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  Subjects -> ELECTRONICS (Total: 207 journals)
Showing 1 - 200 of 277 Journals sorted by number of followers
IEEE Transactions on Aerospace and Electronic Systems     Hybrid Journal   (Followers: 336)
Control Systems     Hybrid Journal   (Followers: 289)
IEEE Transactions on Geoscience and Remote Sensing     Hybrid Journal   (Followers: 236)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 213)
Electronics     Open Access   (Followers: 177)
Advances in Electronics     Open Access   (Followers: 172)
Electronics For You     Partially Free   (Followers: 159)
Electronic Design     Partially Free   (Followers: 157)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 144)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 94)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 92)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 88)
IEEE Transactions on Industrial Electronics     Hybrid Journal   (Followers: 88)
IEEE Transactions on Software Engineering     Hybrid Journal   (Followers: 87)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 81)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 70)
IET Power Electronics     Open Access   (Followers: 69)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 66)
IEEE Embedded Systems Letters     Hybrid Journal   (Followers: 59)
IEEE Transactions on Industry Applications     Hybrid Journal   (Followers: 58)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 57)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 55)
Advances in Power Electronics     Open Access   (Followers: 50)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 46)
IEEE Nanotechnology Magazine     Hybrid Journal   (Followers: 44)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 42)
IEEE Transactions on Biomedical Engineering     Hybrid Journal   (Followers: 36)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 34)
IET Microwaves, Antennas & Propagation     Open Access   (Followers: 33)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 32)
Electronics Letters     Open Access   (Followers: 32)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 32)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 30)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 28)
Microelectronics and Solid State Electronics     Open Access   (Followers: 27)
International Journal of Aerospace Innovations     Full-text available via subscription   (Followers: 25)
Journal of Sensors     Open Access   (Followers: 23)
International Journal of Power Electronics     Hybrid Journal   (Followers: 23)
IEEE Reviews in Biomedical Engineering     Hybrid Journal   (Followers: 21)
IEEE/OSA Journal of Optical Communications and Networking     Hybrid Journal   (Followers: 20)
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 19)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 18)
IET Wireless Sensor Systems     Open Access   (Followers: 18)
IEEE Transactions on Signal and Information Processing over Networks     Hybrid Journal   (Followers: 17)
Journal of Artificial Intelligence     Open Access   (Followers: 16)
Circuits and Systems     Open Access   (Followers: 16)
Archives of Electrical Engineering     Open Access   (Followers: 16)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 16)
International Journal of Control     Hybrid Journal   (Followers: 14)
Advances in Microelectronic Engineering     Open Access   (Followers: 14)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 14)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 13)
IETE Journal of Research     Open Access   (Followers: 13)
IEEE Solid-State Circuits Magazine     Hybrid Journal   (Followers: 13)
International Journal of Advanced Electronics and Communication Systems     Open Access   (Followers: 13)
Nature Electronics     Hybrid Journal   (Followers: 13)
Machine Learning with Applications     Full-text available via subscription   (Followers: 13)
Solid-State Electronics     Hybrid Journal   (Followers: 12)
IEEE Transactions on Broadcasting     Hybrid Journal   (Followers: 12)
IEEE Transactions on Learning Technologies     Full-text available via subscription   (Followers: 12)
IEEE Women in Engineering Magazine     Hybrid Journal   (Followers: 12)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 12)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 12)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 11)
Frontiers in Electronics     Open Access   (Followers: 11)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 10)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 10)
Batteries     Open Access   (Followers: 10)
Superconductivity     Full-text available via subscription   (Followers: 10)
IETE Technical Review     Open Access   (Followers: 9)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 9)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 9)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 9)
ACS Applied Electronic Materials     Open Access   (Followers: 9)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 8)
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 8)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 8)
Journal of Signal and Information Processing     Open Access   (Followers: 8)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 8)
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 8)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 8)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 8)
International Journal of Antennas and Propagation     Open Access   (Followers: 7)
Annals of Telecommunications     Hybrid Journal   (Followers: 7)
IEEE Transactions on Autonomous Mental Development     Hybrid Journal   (Followers: 7)
IEEE Magnetics Letters     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 7)
Open Journal of Antennas and Propagation     Open Access   (Followers: 7)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 7)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 7)
Energy Storage Materials     Full-text available via subscription   (Followers: 7)
Chinese Journal of Electronics     Open Access   (Followers: 7)
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access   (Followers: 7)
Electronic Markets     Hybrid Journal   (Followers: 6)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 6)
International Journal of Electronics     Hybrid Journal   (Followers: 6)
Journal of Electronics (China)     Hybrid Journal   (Followers: 6)
Journal of Field Robotics     Hybrid Journal   (Followers: 6)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 6)
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 6)
Australian Journal of Electrical and Electronics Engineering     Hybrid Journal   (Followers: 6)
EPE Journal : European Power Electronics and Drives     Hybrid Journal   (Followers: 6)
Advanced Materials Technologies     Hybrid Journal   (Followers: 6)
Nanotechnology, Science and Applications     Open Access   (Followers: 5)
IEEE Transactions on Services Computing     Hybrid Journal   (Followers: 5)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 5)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 5)
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 5)
Metrology and Measurement Systems     Open Access   (Followers: 5)
IEEE Pulse     Hybrid Journal   (Followers: 5)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 5)
Journal of Optoelectronics Engineering     Open Access   (Followers: 5)
Batteries & Supercaps     Hybrid Journal   (Followers: 5)
Journal of Power Electronics     Hybrid Journal   (Followers: 5)
Sensors International     Open Access   (Followers: 5)
e-Prime : Advances in Electrical Engineering, Electronics and Energy     Open Access   (Followers: 5)
Materials Today Electronics     Open Access   (Followers: 5)
Networks: an International Journal     Hybrid Journal   (Followers: 4)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 4)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 4)
IEEE Transactions on Haptics     Hybrid Journal   (Followers: 4)
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 4)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 4)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
IETE Journal of Education     Open Access   (Followers: 4)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 4)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 4)
EPJ Quantum Technology     Open Access   (Followers: 4)
Wireless and Mobile Technologies     Open Access   (Followers: 4)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 4)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
Informatik-Spektrum     Hybrid Journal   (Followers: 3)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 3)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 3)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal   (Followers: 3)
Power Electronic Devices and Components     Open Access   (Followers: 3)
Journal of Nuclear Cardiology     Hybrid Journal   (Followers: 2)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Journal of Semiconductors     Full-text available via subscription   (Followers: 2)
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 2)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 2)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 2)
Journal of Information and Telecommunication     Open Access   (Followers: 2)
Advancing Microelectronics     Hybrid Journal   (Followers: 2)
IET Smart Grid     Open Access   (Followers: 2)
IET Energy Systems Integration     Open Access   (Followers: 2)
Transactions on Electrical and Electronic Materials     Hybrid Journal   (Followers: 2)
Energy Storage     Hybrid Journal   (Followers: 2)
IEEE Open Journal of the Industrial Electronics Society     Open Access   (Followers: 2)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 1)
Journal of Electrical Bioimpedance     Open Access   (Followers: 1)
International Journal of High Speed Electronics and Systems     Hybrid Journal   (Followers: 1)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Електротехніка і Електромеханіка     Open Access   (Followers: 1)
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 1)
Edu Elektrika Journal     Open Access   (Followers: 1)
Technical Report Electronics and Computer Engineering     Open Access   (Followers: 1)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 1)
Open Electrical & Electronic Engineering Journal     Open Access   (Followers: 1)
International Journal of Hybrid Intelligence     Hybrid Journal   (Followers: 1)
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access   (Followers: 1)
Solid State Electronics Letters     Open Access   (Followers: 1)
Ural Radio Engineering Journal     Open Access   (Followers: 1)
IEEE Open Journal of Circuits and Systems     Open Access   (Followers: 1)
IEEE Letters on Electromagnetic Compatibility Practice and Applications     Hybrid Journal   (Followers: 1)
Elektronika ir Elektortechnika     Open Access   (Followers: 1)
Automatika : Journal for Control, Measurement, Electronics, Computing and Communications     Open Access   (Followers: 1)
npj Flexible Electronics     Open Access  
Transactions on Cryptographic Hardware and Embedded Systems     Open Access  
Emitor : Jurnal Teknik Elektro     Open Access  
IEEE Solid-State Circuits Letters     Hybrid Journal  
IEEE Open Journal of Industry Applications     Open Access  
IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology     Hybrid Journal  
Journal of Electronic Science and Technology     Open Access  
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Journal of Engineered Fibers and Fabrics     Open Access  
Jurnal Teknologi Elektro     Open Access  
IET Nanodielectrics     Open Access  
Elkha : Jurnal Teknik Elektro     Open Access  
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Jurnal Teknik Elektro     Open Access  
IACR Transactions on Symmetric Cryptology     Open Access  
Acta Electronica Malaysia     Open Access  
Bioelectronics in Medicine     Hybrid Journal  
Problemy Peredachi Informatsii     Full-text available via subscription  
Jurnal Rekayasa Elektrika     Open Access  
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Visión Electrónica : algo más que un estado sólido     Open Access  
Telematique     Open Access  
International Journal of Nanoscience     Hybrid Journal  
Semiconductors and Semimetals     Full-text available via subscription  

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IEEE Transactions on Industry Applications
Journal Prestige (SJR): 1.02
Citation Impact (citeScore): 4
Number of Followers: 58  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0093-9994
Published by IEEE Homepage  [228 journals]
  • IEEE Industry Applications Society Information

    • Free pre-print version: Loading...

      Pages: C2 - C2
      Abstract: null
      PubDate: FRI, 19 JAN 2024 09:17:21 -04
      Issue No: Vol. 60, No. 1 (2024)
       
  • IEEE Transactions on Industry Applications Publication Information

    • Free pre-print version: Loading...

      Pages: C3 - C3
      Abstract: null
      PubDate: FRI, 19 JAN 2024 09:17:21 -04
      Issue No: Vol. 60, No. 1 (2024)
       
  • IEEE Transactions on Industry Applications Information for Authors

    • Free pre-print version: Loading...

      Pages: C4 - C4
      Abstract: null
      PubDate: FRI, 19 JAN 2024 09:17:21 -04
      Issue No: Vol. 60, No. 1 (2024)
       
  • Connect. Support. Inspire.

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      Pages: 1956 - 1956
      Abstract: null
      PubDate: FRI, 19 JAN 2024 09:17:21 -04
      Issue No: Vol. 60, No. 1 (2024)
       
  • Guest Editorial Advances in Energy Conversion, Control, Operation and
           Planning Towards Self-Sustained Highway Transportation Energy System

    • Free pre-print version: Loading...

      Authors: Zhaohao Ding;Payman Dehghanian;Jiangbiao He;Sidun Fang;Mahesh Illindala;Piampoom Sarikprueck;Ali Bidram;
      Pages: 937 - 939
      Abstract: As a major components of modern transportation systems, the highway transportation system is one of the most significant carbon emission contributors in the entire transportation sector. Although there are numerous distributed renewable resources along the highway system, their diversified inherent characteristics and heterogeneous operational conditions present challenges to fully utilize those clean energy resources for the highway transportation system. Towards the carbon neutrality targets, it is important to investigate the integrated multi-energy conversion, control, operation and planning for the self-sustained highway transportation system from an energy-transportation nexus perspective. Therefore, the coordinated interaction of the various components of the highway transportation energy system becomes essential. This entails not only advancements in energy conversion technologies but also the development of intelligent control systems, sustainable operational models, and forward-thinking planning to enable self-sustained energy ecosystems along the highway.
      PubDate: MON, 27 NOV 2023 09:18:52 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Value of Resilience for Self-Sustained Highway Transportation Systems

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      Authors: Xuan Liu;Haoyuan Yan;Debin Zeng;Tianyang Zhao;Zhanglei Guan;Chenghong Gu;
      Pages: 940 - 952
      Abstract: Nowadays, self-sustained highway transportation systems (HTSs) are calling for the inter-operation of road networks, distribution networks (DNs), and electric vehicles (EVs) towards the unexpected impacts inducted by extreme weather events (EWEs). A novel joint resilience assessment scheme is proposed to quantify the resilience of self-sustained HTSs under tropical cyclone (TC) events. The impacts of TCs on transmission lines and highways are formulated using a two-step ambiguity set. In the first step, a multitask learning (MTL) based model with a novel training strategy is proposed to simulate the future TC tracks; the impacts of TCs are then calculated in the second step based on the simulation results. Using the ambiguity set, the self-sustained HTSs resilience assessment problem is formulated based on the dynamic optimal traffic assignment problem, where EVs are integrated as third-party emergency resources before the advent of TCs. This scheme is then formulated as a two-stage distributionally robust optimization (DRO) problem and reformulated as a mixed-integer linear programming (MILP) problem. Case studies have been conducted on a self-sustained HTS consisting of a modified IEEE-14 bus test system with 2 wind farms (WFs) and a 14-node transportation network with 4 charging stations (CSs). Numerical results indicate that the proposed scheme can quantify the resilience of self-sustained highway transportation systems under the joint operation of EVs regarding the unmet travel demand and load-shedding costs. In comparison to the statistical TC forecasting models, the proposed MTL-based model is more accurate and can reduce the system cost in most cases.
      PubDate: MON, 17 APR 2023 10:03:51 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Enhancing Resilience With Electric Vehicles Charging Redispatching and
           Vehicle-to-Grid in Traffic-Electric Networks

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      Authors: Wei Gan;Jianfeng Wen;Mingyu Yan;Yue Zhou;Wei Yao;
      Pages: 953 - 965
      Abstract: Electric vehicles (EVs) can be viewed as both electric loads and a type of mobile storage resource. Effective management and utilization of EVs can yield significant benefits for networks. This article proposes a novel resilience enhancement method for coupled traffic-electric networks with a high penetration of EVs, incorporating two specific strategies in response to contingencies. The first strategy involves rerouting and reselecting charging stations for power-deficient EVs, while the second entails redispatching power-sufficient EVs to the most suitable nearby charging stations to provide grid support through vehicle-to-grid technology. A carefully designed pricing mechanism, which includes imposing additional road congestion tolls and charging station charging fees, is incorporated to facilitate rerouting and charging station reselection for EVs under the user equilibrium principle. Furthermore, a formulation incorporating the two proposed resilience enhancement strategies for coupled traffic-electric networks is presented. This formulation enables coordination between the two networks to capitalize on flexibility derived from sector coupling. A series of linearization techniques are then introduced to transform the original problem into a mixed-integer quadratically constrained programming model. Numerical results based on a coupled network with 20 traffic roads and 21 electric buses are presented to demonstrate the effectiveness of the proposed resilience enhancement method.
      PubDate: THU, 04 MAY 2023 10:07:32 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Deep Reinforcement Learning-Based Spatiotemporal Decision of Utility-Scale
           Highway Portable Energy Storage Systems

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      Authors: Yongkang Ding;Guannan Qu;Xinjiang Chen;Jianxiao Wang;Jie Song;Guannan He;
      Pages: 966 - 975
      Abstract: Mobile charging is an efficient solution to meet peak charging demand on highways. In this article we propose a deep reinforcement learning (DRL)-based approach to maximize the revenue of a utility-scale highway portable energy storage system (PESS) for on-demand electric vehicle charging. We consider a PESS that consists of an electric truck, battery, and charging stations on highways. Actions include the selection of stations and routes, the selection of charging and discharging, and the corresponding charging/discharging power selection. The first two are discrete, while the last is continuous. To deal with the hybrid action space and time-varying state space of PESS, we design an action space, observation space, and reward function according to its characteristics; in addition, we develop a state-of-the-art DRL model for online decision-making considering the uncertainty in the real-time market price of electricity. Through numerical simulations with real-world electricity price data in California, we demonstrate the effectiveness of the proposed method.
      PubDate: WED, 10 MAY 2023 10:02:05 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Coordinated Optimization of Tourist Electric Bus Scheduling and VSC Power
           Dispatching Considering Transportation Influence and PV Accommodation

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      Authors: Bo Zhang;Yujing Zhang;Weidong Chen;Lu Zhang;Wei Tang;Qiming Zhang;
      Pages: 976 - 985
      Abstract: Low voltage distribution networks (LVDNs) are facing challenges on power flow optimization considering the power fluctuation of large-scale PVs. DC interconnected LVDNs were proposed to enhance the capability of power flow dispatching. Tourist Electric Buses (TEBs) have a strong scheduling capability due to large battery capacity and sufficient parking time when waiting for travelers visiting. However, the scheduling of TEBs is limited by the requirement of SOC and the mobility time. This article proposes a coordinated optimization method of TEBs and VSC power outputs in DC-interconnected LVDNs considering TEB schedule requirement and transportation influences on TEB mobility optimization, in order to fully utilize PV outputs. TSN model is established considering the characteristic of TEBs, in order to calculate the mobility time between charging piles and drop-off areas. An optimization model is developed considering power transfer capability of VSC, in order to increase PV accommodation. Simulations studies are performed to verify the proposed method.
      PubDate: FRI, 26 MAY 2023 10:01:27 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Optimal Scheduling of Regional Integrated Energy System Considering the
           Integration of Electric Vehicles and the Life Cycle Assessment Method

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      Authors: Ling Li;Dechang Yang;Zhenghao Liu;Xiaoqing Ji;Nikita Tomin;
      Pages: 986 - 995
      Abstract: With the increasing scale of renewable energy and electric vehicles (EVs), the optimization scheduling of the regional integrated energy system (RIES) is facing new challenges due to the integration of EVs and new energy into the system. To realize the low-carbon economic operation of the RIES, a bi-level optimization scheduling strategy for low-carbon economic operation of the RIES is proposed, which considers EVs' participation and lifecycle carbon emissions, and integrates the electricity market and carbon trading market. Firstly, there are many factors affecting the carbon emissions of EVs and the difficulties in prediction. From the indirect carbon emissions during the use of EVs, the relationship between the carbon emissions of EVs and the charging mode and carbon emission sources is comprehensively analyzed. A carbon emission model of EVs based on the Life Cycle Assessment (LCA) is established in this article. Secondly, the charging model of EVs based on demand response is combined with the electricity market; The carbon emission model of EVs based on the LCA is combined with the carbon trading market, and a bi-level scheduling strategy based on the flexible interaction between carbon and electricity is proposed. Then the strategy is solved to minimize system economic costs and carbon transaction costs. Finally, simulation example analysis is conducted to demonstrate that the proposed strategy can effectively reduce the total charging costs of electric vehicle users, improve the utilization rate of renewable energy, and reduce carbon dioxide emissions, with good economic and environmental benefits.
      PubDate: TUE, 13 JUN 2023 10:01:08 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Resilience Enhancement Method Against Persistent Extreme Weather With Low
           Temperatures in Self-Sustained Highway Transportation Energy System

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      Authors: Fangjian Chen;Mingchao Xia;Qifang Chen;Liu Yang;
      Pages: 996 - 1009
      Abstract: Self-sustained highway transportation energy system (SHTES) means an integrated system that combines multi-energy planning, conversion, control and operation to achieve self-sustained highway transportation energy supply in the context of energy-transportation nexus, which can make full use of renewable natural resources along the highway and reduce operating costs. However, extreme weather and natural disaster may damage the infrastructure of SHTES, seriously threatening the reliable energy supply of multi-energy load. A resilience-oriented strategy is proposed in this article, which aims at strengthening the ability of SHTES against the sustained extreme weather with low temperatures. Firstly, a special SHTES structure including energy router is formulated to improve energy efficiency and reduce carbon emission. Then, taking the freezing rain disaster as an example, we propose a two-stage resilience enhancement method. In the first stage, the pre-disaster proactive preparedness is taken to support the operation of the SHTES in disaster. In the second stage, the uncertain system topology state transition driven by the evolution of disasters can be modeled as a Markov process to help highway transportation energy management center (HTEMC) make decisions with a view of foresight. Specifically, the state transition probability matrix can be calculated by the weather information-based component fault model. The simulation results indicate that the proposed method can soften the impact of persistent extreme weather with low temperatures and effectively enhance the resilience of the SHTES.
      PubDate: THU, 29 JUN 2023 10:02:00 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • An Energy Scheduling Scheme for Highway Microgrids Virtually Networked by
           Electric Operation and Maintenance Vehicles

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      Authors: Shiwei Xia;Xiaolong Zhang;Letian Yuan;Ting Wu;Gengyin Li;Mohammad Shahidehpour;
      Pages: 1010 - 1022
      Abstract: Promoting the penetration level of renewable energy in highways plays a key role in realizing a low-carbon and efficient transportation system. In this regard, this paper proposes an energy scheduling scheme considering the flexibility of Electric Operation and Maintenance Vehicles (EOMVs) to enhance the highway microgrids’ operation economics and renewable energy self-sufficiency rate. First, a differentiated delay-time based dynamic time-space network (TSN) model is established to fully exploit the temporal and spatial flexibility of EOMVs. Afterward, electric vehicle (EV) battery swapping demand in highway service areas, the battery charging/discharging and inventory coupling, the operation and maintenance tasks of EOMVs, and diesel generators (DG) output constraints are considered to establish an energy scheduling scheme for minimizing the total of the power generation cost, the EOMVs’ transportation cost, the wind/photovoltaic power curtailment cost, and the EV swapping cost in highway microgrids. In such a way, the navigation route of EOMVs, the charging/discharging of swappable batteries and DG outputs are optimized with energy mutually supported among highway microgrids. Finally, the effectiveness of the proposed energy scheduling scheme is verified by the simulation results of practical highway microgrids.
      PubDate: MON, 03 JUL 2023 10:03:47 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Elite Genetic Algorithm Based Self-Sufficient Energy Management System for
           Integrated Energy Station

    • Free pre-print version: Loading...

      Authors: Lize Liu;Xiaoling Su;Laijun Chen;Shuai Wang;Jiawei Li;Siwei Liu;
      Pages: 1023 - 1033
      Abstract: In order to solve adverse effects caused by disorderly hydrogen refueling behavior of hydrogen fuel cell vehicles (HFCVs) and output power uncertainty of renewable energy sources on integrated energy stations, this article proposes a self-sustained energy management system based on elite genetic algorithm for integrated energy stations (IESs) to support the low carbon and economical operation of self-sustained highway transportation energy system. First, a detailed IES model is developed to simulate dynamic interaction between utility grid, hydrogen network and transportation network. Second, a two-layer energy optimization management system is established. The upper layer forms user behavior modes of HFCVs to reduce its peak-valley difference and hydrogen refueling cost. The lower layer gives energy management strategies and feeds back to the upper layer based on HFCVs refueling behavior patterns to improve self-sustain rate and reduce carbon emission costs of IESs, meanwhile IESs provide auxiliary services according to their operating status. The simulation results verify the feasibility and correctness proposed IESs model and its self-sustained energy management system.
      PubDate: WED, 05 JUL 2023 10:00:49 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • A Hierarchical Multi-Timeframe Multi-Energy Sharing Framework for a
           Self-Sustained Energy-Transportation Nexus

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      Authors: Kuan Zhang;Yuxin Luo;Yu Fu;Nian Liu;
      Pages: 1034 - 1047
      Abstract: This article proposes a hierarchical multi-timeframe multi-energy sharing framework for the peer-to-peer hydrogen (H2)-electricity trading among the integrated hydrogen-electricity energy stations (IHESs) scattered at the freeway traffic system. Specifically, the upper layer aims to increase the IHESs’ day-ahead incomes while determining the amount of shared H2 among IHESs on long timeframes, where the H2 sharing is modeled as a distributionally robust optimization (DRO) problem. The obtained shared amount of H2 from the upper layer is served as the optimal reference to be followed in the lower level. The objective of the lower layer is to maximize the real-time profits of IHESs with rolling horizon-based DRO model, where the flexible electricity sharing is coordinated and optimized on small timeframes to overcome the uncertain sources and slow dynamic characteristics of shared H2 transportation. A model-data driven forecasting approach containing the partial differential fluid dynamic model and long short-term memory (LSTM) neural network is formulated to estimate the diversified time-varying load demands at IHESs. Moreover, an ADMM-based distributed pricing strategy is developed to obtain the incentive compatible prices for multi-energy sharing, and a closed-form optimal price solution is derived to accelerate the convergence speed. Comparative studies have demonstrated the superior performance of the proposed methodology on the improvement of the self-sustained efficiency and economic benefits for the energy-transportation nexus.
      PubDate: TUE, 25 JUL 2023 10:01:58 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Two-Level Optimization Model of Integrated Energy System Based on Dynamic
           Pricing Mechanism

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      Authors: Jian Zhou;Li Zhang;Guanya Zhang;
      Pages: 1048 - 1057
      Abstract: The interests of integrated energy system operators and energy users in road transportation need a more reasonable pricing mechanism to achieve mutual benefit. Taking highway transportation energy system as the research object, this article proposes a two-level optimization model based on dynamic pricing mechanism. Firstly, A two-level optimization model of energy system operators and users, dominated by the size and order of equipment output, has been established. The Monte Carlo method is used to simulate the random load of electric vehicles for further scheduling. Then, a new dynamic pricing mechanism is constructed, with the upper level pricing based on the output of gas boilers, waste heat boilers, new energy, and gas turbines and their low-carbon characteristics. The lower level participates in the optimal scheduling of the upper level, based on price and its own economy. The model constantly updates the price and load distribution to achieve mutual benefit. CPLEX is used to iteratively solve the two-level programming model, and the joint optimal solution of the system is selected according to the joint optimal discrimination mechanism. The effectiveness of the model and method is verified through comparison with time-of-use electricity prices.
      PubDate: TUE, 26 SEP 2023 09:16:51 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Battery Swapping Dispatch for Self-Sustained Highway Energy System Based
           on Spatiotemporal Deep-Learning Traffic Flow Prediction

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      Authors: Yuxin Sun;Yiqun Li;Stefan Borozan;Guibin Wang;Jing Qiu;Goran Strbac;
      Pages: 1058 - 1070
      Abstract: Due to the complexity of traffic flow and the stochastic swapping behavior of electric vehicles (EVs), efficient battery dispatch is challenging. Therefore, the battery swapping dispatch framework based on traffic flow prediction is proposed to overcome this inconvenience. The framework is solved by minimizing the total transportation cost and satisfying the EV battery swapping requirement. Naturally, precise traffic flow prediction plays a vital role in efficient battery dispatch. Therefore, this article designs a deep learning prediction framework by leveraging the graph convolutional network (GCN) and the temporal convolutional network (TCN), named Spatiotemporal traffic flow network (STFNet). GCN is applied to learn the topology characteristic of the daily spatiotemporal traffic, which enables STFNet to capture the spatial feature. TCN is developed to acquire the daily traffic flow temporal dependence. Additionally, a pre-partition method based on K-means clustering is applied to improve the effectiveness of the battery dispatch framework. The experimental results indicate that the proposed battery dispatch framework is skillful. Due to the precise prediction of STFNet, the battery swapping dispatch based on STFNet prediction is the most economical, achieving a minimum of 25.82% reduction in the total transportation cost compared to benchmark models. Furthermore, the impact of the pre-partition method has been proven in the case of studies with a huge routing distance declining, dramatically reducing the total transportation cost and making the dispatch more reasonable.
      PubDate: TUE, 03 OCT 2023 09:18:25 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Investigation of Five-Phase Flux-Switching Permanent Magnet Machines for
           EV and HEV Applications

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      Authors: Xiaofeng Zhu;Wentao Huang;
      Pages: 1071 - 1082
      Abstract: As a member of stator permanent magnet (PM) brushless machines, flux-switching (FS) PM machine features outstanding advantages, e.g., robust rotor structure, easy temperature management, high torque density, etc. In this article, the five-phase FSPM machines for electric vehicle (EV) and hybrid electric vehicle (HEV) applications are investigated. Firstly, the working principle of such machine is analyzed by air-gap field modulation theory. Then, the feasible slot/pole combination is discussed, considering flux leakage, back electro-magnetic force (EMF) quality and unbalanced magnetic force (UMF). Besides, in order to further choose the recommendable slot/pole combination, the torque performances are studied and compared by taking the 20-stators-slot FSPM machines as examples, such as rated torque, overload capability, flux weakening capability and fault tolerance capability. Further, in order to optimize the slot/pole combination which suffers from severe UMF, two different techniques for UMF reduction are proposed, including chamfering both in stator and rotor side. Finally, finite element analysis is employed to verify the analytical analyses. Meanwhile, a 20/18 prototyped machine is manufactured and tested. It is found that the experimental results verify the effectiveness of the analytical analyses.
      PubDate: WED, 10 MAY 2023 10:02:03 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • An Integration Scheme for Highway Rest Area Integrating the Distributed
           Photovoltaic Generation and Energy Storage

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      Authors: Bowen Li;Huiru Sun;Jie Lou;Kaiqi Sun;Zhengfa Zhang;Yuanyuan Sun;
      Pages: 1083 - 1092
      Abstract: With the large-scale expansionary of electric vehicles (EVs), charging facilities on highway have also been developed rapidly as supporting services, providing convenient and fast charging services for electric vehicle users. Due to the limited number and capacity of charging facilities, it is difficult to meet diverse queue waiting time needs of EV users during peak charging periods. Meanwhile, considering the integration of distributed photovoltaic and distributed energy storage system (DPV-DESS) on highway, this paper aims at proposing a strategy for the highway to coordinate multiple resources and meet the diverse charging demand of EVs. In this paper, a highway integration scheme with DPV-DESS is established to maximize the EV charging simultaneity and EV users’ satisfaction while achieving the efficient utilization of DPV-DESS. Firstly, based on the DPV-DESS configuration, the model of photovoltaic (PV), energy storage and EV charging parameters are built. Secondly, considering PV output characteristics and the diverse charging needs, a two-layer optimization model is put forward. In the upper layer, multi-source coordination optimization model is proposed to realize efficient utilization. In the lower layer, an orderly charging strategy is raised for EVs senseless charging. Finally, case studies have been conducted on a self-sustained DPV-DESS consisting of a modified test system with 20 charging piles. Numerical results indicate that the proposed scheme can maximize the EV users’ satisfaction while minimizing the operating cost on the premise of the self-sustained highway transportation energy system operation.
      PubDate: MON, 30 OCT 2023 09:19:29 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Research and Design of an Optimal Management Strategy for Simultaneous
           Wireless Power and Information Transmission for Highway Vehicles

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      Authors: Li Ji;Kaixin Yan;Jingxuan Ma;Ming Zhang;
      Pages: 1093 - 1104
      Abstract: Mobile edge computing (MEC) provides a new solution for meeting the growing energy and computational demands of road transportation systems. However, it is difficult for MEC alone to satisfy the high associated computational requirements. Therefore, a cloud-assisted mobile edge computing (CAMEC) framework is used in this paper to investigate the problem of computation and offloading strategies for tasks. First, to address the cost of roadside unit (RSU) deployment, the use of vehicles being charged (VCs) as edge servers is proposed. Additionally, to minimize the system latency, this study considers the problem of maximizing the channel capacity for the simultaneous wireless transmission of power and information (SWTPI). Based on this, a computational offloading model is developed to minimize a weighted sum of system delay and energy consumption, with the available server and device resources and the maximum delay as constraints. To solve this multivariate nonconvex problem, an iterative algorithm based on successive convex approximations and alternating iterations is proposed. Simulation results show that under the offloading scheme proposed in this paper, the system cost is reduced by approximately 30% compared to that with MEC only, indicating that the scheme is effective at reducing the weighted sum of delay and energy consumption.
      PubDate: WED, 01 NOV 2023 09:18:16 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • A Computationally Efficient Model Predictive Control Method for Dual
           Three-Phase PMSM of Electric Vehicle With Fixed Switching Frequency

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      Authors: Zhifeng Zhang;Quanzeng Sun;Qingyi Zhang;
      Pages: 1105 - 1116
      Abstract: Aiming at the problems of large harmonic current, unfixed switching frequency and heavy calculation burden in the model predictive current control (MPCC) methods of dual three-phase permanent magnet synchronous motor (DT-PMSM). This article presents a computationally efficient MPCC method with a fixed switching frequency. Firstly, the virtual voltage vectors (V3s) are synthesized by two large vectors and two medium-small vectors. The V3s effectively reduce the harmonic currents, and the goal of the synthetic V3 is that the harmonic current in the x-y subspace is zero. Therefore, the weighting factor of the harmonic term is eliminated in the cost function. Secondly, an optimal voltage vector selection method is designed to reduce the candidate voltage vectors in the control set and relieves the calculation burden. In addition, to further reduce ripple current and torque ripple, the duty cycle modulation method is introduced to calculate the dwell time of the V3. The zero vector is inserted in the middle and both sides of the V3s to achieve the purpose of fixing the switching frequency. Finally, the effectiveness of the proposed method is verified by experiments.
      PubDate: MON, 22 MAY 2023 10:03:22 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Exploring Symmetry-Induced Divergence in Decentralized Electric Vehicle
           Scheduling

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      Authors: Weijia Chen;Jianxiao Wang;Tiance Zhang;Gengyin Li;Yihang Jin;Leijiao Ge;Ming Zhou;Chin-Woo Tan;
      Pages: 1117 - 1128
      Abstract: Due to the low computational efficiency and high communication pressure caused by centralized control, decentralized coordination of electric vehicles (EVs) has become a research hotspot in recent years. However, the integration of numerous EVs with homogeneous parameters brings unprecedented challenges for the optimal scheduling of the power system. To explore symmetry-induced divergence in decentralized electric vehicle scheduling, the established centralized optimization scheduling model of electric vehicles is decomposed into a distributed optimization model by Lagrange relaxation, achieving parallel control of each EV aggregator (EVA). To solving the oscillation caused by parameter symmetry in the process of optimization, we propose a convergence acceleration algorithm based on a perturbation function, which is a random distribution function used to break parameter symmetry within an acceptable calculation error range. On the premise of sensitivity analysis, a closed form of the perturbation limit is theoretically derived. Case studies based on different scales of users validate the effectiveness and computational efficiency of the proposed method.
      PubDate: TUE, 23 MAY 2023 10:01:28 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Contribution to V2G System Frequency Regulation by Charging/Discharging
           Control of Aggregated EV Group

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      Authors: Bo Jie;Jumpei Baba;Akiko Kumada;
      Pages: 1129 - 1140
      Abstract: As the number of electric vehicles (EV), a new category of clean and environmentally friendly transportation means, increases yearly, which not only puts forward new requirements for the modernization of the infrastructure of transportation system, but also demands that the impact on power system be given significant consideration. The increasing of EV utilization in transportation sector and renewable energy integration, such as, PV panel, in local power grid exacerbates system frequency fluctuation. Regulation of system frequency deviation by EV battery storage charging/discharging is a crucial issue for the time being. In this article, a power grid model with a high proportion of PV power is constructed, numerical simulation using time series data is carried out to observe the contribution of the charging/discharging control of aggregated EV group to vehicle to grid (V2G) system frequency regulation. By this way, constructive suggestions are given for the development of charging stations and EV charging/discharging plan, so that the transportation system and power system can be better coordinated and integrated.
      PubDate: THU, 06 JUL 2023 10:02:24 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • A Model Predictive Control-Based Voltage Optimization Method for Highway
           Transportation Power Supply Networks With Soft Open Points

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      Authors: Wentao Huang;Congzhe Gao;Ran Li;Rohit Bhakar;Nengling Tai;Moduo Yu;
      Pages: 1141 - 1150
      Abstract: Increasing renewable energy penetration exacerbates voltage violation in highway transportation power supply networks (HTPSNs). The technique of flexible connectivity based on soft open points (SOPs) could improve the controllability and voltage stability of the network. However, the generally used voltage control of SOPs may be too sluggish to accommodate the frequent voltage fluctuations and requires further investigation. This article proposes a real-time model predictive control (MPC)-based voltage optimization method for SOPs in HTPSNs. Combining the sensitivity analysis and the operational constraints of the network with SOPs, a localized real-time optimization model is established. With the rolling of the control horizon, the SOPs regulate the voltage and optimize the power flow at a time scale of seconds. Using simply the voltage at the connected node of the SOPs, the proposed method can significantly enhance the voltage stability of the HTPSNs and decrease power losses under the rapid fluctuations of the network voltage. To further improve the performance of voltage control, the optimization model is modified through feedback correction. The case studies demonstrate the effectiveness of the proposed method under different scenarios.
      PubDate: TUE, 18 JUL 2023 10:02:25 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Power Regulation of Islanded PV-Battery DC Microgrid With Seamless
           Transition

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      Authors: Hao Pan;Peng Cheng;Hufu Zhao;Jian Huo;Limin Jia;Qingmin Li;
      Pages: 1151 - 1159
      Abstract: In this article, a power regulation for islanded PV-battery DC microgrid with seamless transition is proposed under sudden load changes. In the power regulation, there are two modes, mode 1 for normal operation and mode 2 for the case where the load power is greater than the PV output, using droop control of PV to maintain the bus voltage and constant voltage control of energy storage to maintain the bus voltage, respectively. Mode 1 ensures that the battery is in a stable charging state and avoids frequent charging/discharging of battery. Mode 2 can maximize the use of PV energy. A seamless switching strategy without communication between the two modes is also established to suppress the fluctuation of bus voltage through the cooperation of PV and energy storage units, and a suitable switching timing is selected to avoid the sudden change of power during the switching process. Finally, the effectiveness and feasibility of the proposed control strategy is verified by the OPAL-5700 hardware-in-loop simulation platform.
      PubDate: THU, 08 JUN 2023 10:02:01 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Comprehensive Optimization of ZVS Variable Frequency Control for SiC/Si
           HANPC Converter

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      Authors: Zhicheng Cai;Yan Du;Jianhui Su;Xiangzhen Yang;Yong Shi;Jian Zhang;
      Pages: 1160 - 1171
      Abstract: The growing demand for high-efficiency power converters with silicon carbide (SiC) devices at high switching frequencies has fueled an interest in non-auxiliary circuit-based soft switching techniques, particularly the variable switching frequency control for zero-voltage switching (VF-ZVS). Besides increasing the Total Harmonic Distortion (THD), applying the full ZVS range to three-phase SiC/Si Hybrid Active Neutral Point Clamped (HANPC) converters leads to a rise in conduction loss. This issue is exacerbated by the use of Si IGBT, as it generates significantly more conduction loss than SiC MOSFET in medium and small power HANPC. Consequently, a power loss optimized VF-ZVS (OVF-ZVS), based on a precise loss model, is proposed to enhance efficiency by considering the effect of the current ripple on device loss. This OVF-ZVS optimizes the switching frequency to minimize the total loss of three-phase switching devices across all load ranges. Meanwhile, the variable switching frequency range and LCL parameters are optimized to strike a balance between superior output current quality, power density, etc. Simulation and experimentation using a 10 kW HANPC converter prototype illustrate the effectiveness of the proposed comprehensive optimization, further highlighting the reduction in THD and device loss.
      PubDate: MON, 18 SEP 2023 10:04:27 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Hybrid Control Strategy of Series Resonant DC/DC Converter for Realizing
           Active Soft Switch

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      Authors: Tao Zhang;Hui Wang;Bai Guo;Aoyu Fang;Jichen Qu;
      Pages: 1172 - 1182
      Abstract: This paper presents a novel active soft switch control strategy for full bridge series resonant DC/DC converter with phase-frequency hybrid modulation. The proposed control strategy has the capability of wider load range and higher efficiency (especially under light loads) compared with frequency modulation. Three possible work modes and their loss profiles are analyzed by means of the state trajectory method. The principle of the active soft switch is revealed, and its mechanism of enhancing efficiency and extending load range as opposed to frequency modulation is interpreted. The general state space averaging method is used to model power stage, modulation stage and output stage, and the control strategy for realizing active soft switch is designed. Comparisons between proposed strategy and frequency modulation in terms of load range and efficiency are implemented. Simulation and experiment validate the effectiveness of the control strategy.
      PubDate: THU, 28 SEP 2023 09:17:21 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Bidirectional ZVS Operation of All Switches for a DAB Converter Over a
           Full Range of Loads With Optimized Current Stress

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      Authors: Xiangzhen Yang;Jinxiu Wang;Yan Du;Can Liu;Tao Zhang;Jian Zhang;
      Pages: 1183 - 1195
      Abstract: All-switches zero voltage switching (ZVS) and lower current stress are the most important challenges for improving the efficiency of dual-active-bridge (DAB) converters operating in the bidirectional full-load range and wide voltage range applications. Triple-phase-shift (TPS) has three control degrees of freedom and it is a more flexible way to extend the ZVS range in all kinds of operating conditions. In order to improve the efficiency of DAB converters, a new optimal current stress in TPS (OCS-TPS) control is proposed to minimize the current stress as well as achieve all-switches ZVS within the bidirectional full-load range and wide voltage range applications. Firstly, seven specific switching modes satisfying the ZVS conditions under step-up and step-down are selected from 12 TPS switching modes. Secondly, the issue of current stress minimization is turned into an extreme optimization problem with equality constraints of desired transmission power and inequality constraints of ZVS conditions in selected switching modes. The Karush-Kuhn-Tucker (KKT) algorithm is employed to solve this optimization issue. Then two switching modes are chosen to form the high-load range ZVS and low-load range partial-switches ZCS/ZVS in the case of step-down and step-up operations respectively. Therefore, the phase-shift ratios of selected switching modes in the low-load range are further optimized by adding an offset value to achieve all-switches ZVS. Finally, the effectiveness of the proposed strategy is verified by the experimental results.
      PubDate: TUE, 11 JUL 2023 10:01:37 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Robust Emergency Preparedness Planning for Resilience Enhancement of
           Energy-Transportation Nexus Against Extreme Rainfalls

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      Authors: Zhihao Hua;Bin Zhou;Siu Wing Or;Jie Zhang;Canbing Li;Juan Wei;
      Pages: 1196 - 1207
      Abstract: This article proposes a robust emergency preparedness planning (EPP) scheme to optimally pre-position diverse mobile emergency resources (MERs) in staging locations and perform proactive network reconfiguration for resilience enhancement of energy-transportation nexus (ETN) against extreme rainfalls. Based on rainfall-runoff simulation with hydrodynamic partial differential equations, a risk identification approach for flood-prone transportation modeling is developed for vehicle travel time estimation and MER routing optimization. To handle uncertainties in line outages and flooded roads incurred by extreme rainfalls, a tri-level robust EPP model is proposed to determine the optimal emergency preparedness plan immunized against the worst-case realization of uncertainties. Furthermore, a tailored solution method combining nested column-and-constraint generation algorithm with multiple linearization techniques is devised to cope with the proposed nonlinear robust EPP model. Comparative studies have validated the effectiveness of the proposed scheme for resilience enhancement of the ETN confronted with extreme rainfall disasters.
      PubDate: TUE, 09 MAY 2023 10:02:15 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Low Carbon Planning of PV-Charging Stations for Self-Sustained Highway
           Transportation Energy System Considering the Retirement of Gas Stations

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      Authors: Guanchen Yu;Xian Zhang;Hong Wang;Yu Zheng;Edward Chung;Rongwu Zhu;
      Pages: 1208 - 1218
      Abstract: With the pressure of energy crisis, how to achieve low carbon and self-sustaining operation of highway transportation network (HTN) has become an emerging research topic. In the current HTN, fuel vehicles (FVs) and electric vehicles (EVs) form a mixed traffic flow together. In this context, a novel model is proposed for the planning of energy facilities in HTN, including the construction of charging stations and the retirement of gas stations, which takes into account not only the balance of traffic flow but also environmental factors in the planning process. Meanwhile, the construction of charging stations leads to the coupling of HTN and distribution network (DN). In order to further achieve the goal of carbon reduction, a planning framework of low carbon facilities in the charging system is proposed, including the installation of photovoltaic (PV) panels and carbon capture and storage (CCS) systems. Finally, the rationality of the proposed planning method is verified by case studies.
      PubDate: MON, 05 JUN 2023 10:02:35 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Collaborative Planning for Hybrid Refueling Stations With PV Power in
           Highway Networks

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      Authors: Mingchao Xia;Yiming Xian;Qifang Chen;
      Pages: 1219 - 1228
      Abstract: Battery electric vehicles (BEVs) and fuel cell vehicles (FCVs) are ideal technologies for highway transport to achieve zero emissions, and their widespread adoption in highway networks require sufficient available hybrid refueling stations (HRSs). However, existing planning models for HRSs tend to focus on the interior of the city, the research on the planning of HRSs in highway networks, as well as the optimal allocation of hydrogen that can exist between HRSs is usually ignored. This article proposed a collaborative planning method for HRSs in highway networks that included photovoltaic (PV) and hydrogen allocation. First, based on the Floyd algorithm and the Monte Carlo algorithm, this article proposed a charging demand simulation method for HRSs in highway networks. Then we proposed an HRSs energy allocation method using hydrogen as backup mobile energy which aims to realize the cross-space energy dispatch of multi-site PV power generation and improve the energy supply reliability of the HRSs. Finally, based on the above research, considering the safety constraints of the power system along the highway network and the installed capacity constraints of the PV power generation system, we proposed an HRSs planning model including electric-hydrogen conversion devices and storage systems. This method minimizes the transportation cost of hydrogen by rationally planning the amount of hydrogen tube trailers (HTTs) and transportation routes, realizes cross-space energy scheduling of multi-site PV power generation, and thereby improving the energy supply reliability of HRSs and the consumption rate of PV power generation. The case study indicates that compared with the traditional method, the planning method proposed in this article reduces the operating cost by 32.5%, and the total cost decreases by 8.5%, with the PV power consumption rate along the highway network also improved to a certain extent.
      PubDate: MON, 03 JUL 2023 10:03:47 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Expansion Planning of Soft Open Points Based Distribution System
           Considering EV Traffic Flow

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      Authors: Yichen Shen;Shenxi Zhang;Maosheng Ding;Haozhong Cheng;Canbing Li;Dundun Liu;
      Pages: 1229 - 1239
      Abstract: Regarding distribution systems coupled with transportation networks, this study proposes an expansion planning approach to minimize various costs with respect to soft open point (SOP) based distribution system and electric vehicle (EV) navigation. An energy consumption model of EV that considers traffic flow is developed to analyze charging behaviors of EVs. Subsequently, the EV average speed and related energy consumption is estimated to generate optimal charging routes. The proposed model of the EV energy consumption can help to minimize the cost of navigating EVs along the transportation network according to the traffic flow. Referring to the distribution system, the total cost associated with the investment and maintenance of network assets as well as subsequent operations is optimized. Hereafter, an expansion planning model of distribution system considering EV navigation is established. A relaxation approach is employed through which the prescribed nonconvex mixed-integer nonlinear planning model is converted into the form of mixed-integer second order cone programming that can be efficiently solved by commonly used solvers. A 54-bus distribution system coupled with a 35-node transportation network is employed in the case study section to verify the effectiveness of the proposed method. The rationality of considering SOP deployment and EV navigation is validated.
      PubDate: MON, 10 JUL 2023 10:03:05 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Electrochemical Parameter Identification for Lithium-Ion Battery Sources
           in Self-Sustained Transportation Energy Systems

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      Authors: Yuxuan Gu;Jianxiao Wang;Yuanbo Chen;Kedi Zheng;Zhongwei Deng;Qixin Chen;
      Pages: 1240 - 1254
      Abstract: Lithium-ion battery (LIB) sources have played an essential role in self-sustained transportation energy systems and have been widely deployed in the last few years. To realize reliable battery maintenance, identifying its electrochemical parameters is necessary. However, the battery model contains many parameters while the measurable states are only the current and voltage, inducing the identification inherently an ill-conditioned problem. A parameter identification approach is proposed, including the experiment, model, and algorithm. Electrochemical parameters are first grouped manually based on the physical properties and assigned to two sequenced tests for identification. The two tests named the quasi-static test and the dynamic test, are compressed on time for practical implementation. Proper optimization models and a sensitivity-oriented stepwise (SSO) optimization algorithm are developed to search for the optimal parameters efficiently. Typically, the Sobol method is applied to conduct the sensitivity analysis. Based on the sensitivity indexes, the SSO algorithm can decouple the mixed impacts of different parameters during the identification. For validation, numerical experiments on a typical NCM811 battery at different life stages are conducted. The proposed approach saves about half the time finding the proper parameter value. The identification accuracy of crucial parameters related to battery degradation can exceed 95%. Case study results indicate that the identified parameters can not only improve the accuracy of the battery model but also be used as the indicator of the battery SOH.
      PubDate: MON, 20 MAR 2023 10:06:56 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Hybrid LLC Resonant Converter With Partial-Power Auxiliary Unit for
           Improved Performance

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      Authors: Bo Hu;Zipeng Ke;Chao Zhang;Jun Wang;Minmin He;Haiyan Zhu;Zheng John Shen;
      Pages: 1255 - 1267
      Abstract: DC-DC converters used in on-board chargers (OBC) of electric vehicles need to meet the requirements of high efficiency, wide output range, and electrical isolation. In this article, a partial-power processing topology with a wide output range is proposed to overcome the drawbacks of traditional single-stage and two-stage LLC converters. The LLC resonant converter operates near the resonant frequency to maintain high efficiency. While only the partial power is processed by the Buck converter to offer the wide-range output voltage capability. The triangular current mode (TCM) operation is implemented in the Buck converter to minimize the efficiency sacrifice. In addition, to reduce the adverse effect of the second harmonic voltage ripple (SHVR) generated by the AC port on the LLC resonant converter in OBC. A ripple compensation method is proposed to eliminate the SHVR of the LLC resonance converter. Through the dual predictive control for the Buck converter, the SHVR of the LLC resonant converter is offset by the Buck converter. A 2 kW rated experimental prototype is designed to convert 400 V wide input to 200-500 V output. The prototype demonstrates more than 96% efficiency from 30% load to full load at 60-120 V input and a 98.2% peak efficiency.
      PubDate: TUE, 30 MAY 2023 10:01:24 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Electromagnetic-Thermal-Stress Efforts of Stator-Casing Grease Buffers for
           Permanent Magnet Driving Motors

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      Authors: Longnv Li;Gaojia Zhu;
      Pages: 1268 - 1276
      Abstract: Driving motors are one of the most critical components in modern electrified transportation systems, deciding directly the system's working reliability and controllability. To extend the life-cycle of the driving motors while operating them with enough torque output, the temperature rise maintenance techniques have attracted extensive research attention. This article presents a novel stator-casing fitting approach by filling grease materials into the assembly gap between the dovetail-groove-fitted stator core and motor shell of PMSMs. The grease-filled dovetail-groove-fitted structure can reduce effectively the thermal resistance between the machine's internal components and the external coolants, and can also relieve the stress-caused magnetic performance regressions of the electrical steel sheets laminating the stator core. In addition, due to both the thermal conduction enhancement and the stress-buffering effect, the deformation occurring in stator cores can also be reduced, which is helpful to guarantee the machine's precision. Therefore, the electromagnetic, thermal, and stress-deformation performances in the PMSM can all be improved by using grease buffers filled between stator cores and motor casings. To validate the electromagnetic-thermal-stress efforts of the buffers on the prototype together with the simulation methodologies, a 44-kW 6000-rpm line-started PMSM is taken as the reference machine, and a multi-physical coupled model of the problem is numerically calculated. The influences of the grease properties on the machine's working performances and temperature rises are investigated through comparative analyses. Finally, the numerical calculation results are compared with experimental ones to validate their effectiveness.
      PubDate: MON, 03 JUL 2023 10:03:47 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • PEMFC Fault Diagnosis Based on an Equivalent Circuit and OS-ELM Framework

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      Authors: Yong Shi;Wei He;Bao Xie;Yan Du;Xiangzhen Yang;Jianhui Su;
      Pages: 1277 - 1287
      Abstract: Most current proton exchange membrane fuel cell (PEMFC) fault diagnosis models are not updated after offline training is completed, so they cannot learn new data features. For this problem, a PEMFC fault diagnosis model based on an equivalent circuit and an online sequential extreme learning machine (OS-ELM) framework is proposed. Under different operating conditions, the range of equivalent circuit element values is different, which is conducive to fault diagnosis. Element values constitute a dataset, from which OS-ELM is used to learn data features, and PEMFC fault diagnosis and isolation can be accomplished. OS-ELM has online learning capability. During the operation of PEMFC, equivalent circuit fitting is performed on multiple sets of sample data obtained using electrical impedance spectroscopy (EIS). Optimized fuzzy C-means (FCM) is used to cluster and partition sample data for online updating of OS-ELM models. The experimental results show that the proposed PEMFC fault diagnosis model not only has the speed and accuracy of fault diagnosis but also has the ability to learn fault characteristics online.
      PubDate: FRI, 08 SEP 2023 10:01:49 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Electrical Trees of Silicone Gel Encapsulation Materials in Power
           Electronic Modules Self-Healing Properties and Influencing Factors

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      Authors: Jian Wang;Chen Chen;Haosheng Yan;Wei Wang;Liang Zou;Li Zhang;
      Pages: 1288 - 1297
      Abstract: Electric tree is a dendritic channel due to partial discharge, which is a more common form of failure in the insulation system of power electronic modules, and silicone gel is widely used in the package insulation of power electronic modules. On this basis, this article conducts experiments on the growth of electric trees at different frequencies, investigates the initiation and propagation mechanisms of electric tree in silicone gels at high frequencies, and analyzes the mechanism of the effect of frequency on the growth characteristics of electric trees. Furthermore, the self-healing experiments of electric trees at different temperatures and component ratios were carried out to investigate the self-healing behavior of electric trees in silicone gels and its influence mechanism. The experimental results show that Maxwell stress is the main cause of electric tree initiation at high frequencies, and the propagation characteristics of electric trees in silicone gels are different from those of conventional dielectrics. Self-healing in silicone gels can be classified into types I and II, which occur respectively during electric tree propagation and after withdrawal of voltage, and type II self-healing can be further classified into physical and chemical self-healing. The effects of temperature and A-component content on the self-healing properties are also investigated in this article.
      PubDate: MON, 10 JUL 2023 10:03:05 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • High-Temperature Failure Mechanism and Lifetime Assessment of Silicone Gel
           Package Insulation for High-Power Electronic Devices Based on Pyrolysis
           Kinetics

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      Authors: Wei Wang;Yanfeng Gong;Hanwen Ren;Jian Wang;Qingmin Li;
      Pages: 1298 - 1309
      Abstract: High temperature tends to be one principal failure cause of silicone gel package insulation in high-power electronic devices, even leading to equipment damage under severe conditions. To clarify the aging characteristics and failure mechanism of silicone gel package insulation of high-power IGBT devices under the high-temperature scenario, this article carries out experiments on silicone gel material samples by accelerated thermal aging procedures at 200°. The experimental results show that temperature has a significant effect on the physicochemical properties of silicone gel. Further, molecular dynamics simulations are conducted to verify the high-temperature degradation characteristics of the gel. Finding the main cause of silicone gel package insulation failure under high-temperature is the random degradation of the silicone backbone into small molecule cyclosiloxanes. Finally, the Lifetime assessment model was established based on the pyrolysis kinetics and insulation failure mechanism. The unaged silicone gel's pyrolysis activation energy and insulation failure temperature were measured at 125.8 kJ/mol and 453 °C, respectively. The evaluation results show that the package insulation life decreases by about 60% for every 10 °C increase in temperature. The above achievement of this study presents a theoretical and methodological basis for reliable assessment of the insulation status of silicone gel package insulation for high-power electronic devices under high-temperature.
      PubDate: WED, 23 AUG 2023 10:02:46 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Demand and Sustainability Analysis for A Level-3 Charging Station on the
           U.S. Highway Based on Actual Smart Meter Data

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      Authors: Anders Stenstadvolden;Lane Hansen;Long Zhao;Mohammad Heidari Kapourchali;Wei-Jen Lee;
      Pages: 1310 - 1321
      Abstract: Over the next five years, the U.S. will deploy DC fast charging stations along its interstate highway system under the National Electric Vehicle Infrastructure (NEVI) formula program. The large-scale deployment of NEVI charging stations will significantly increase charging demand, posing challenges to power systems. Thus, understanding the charging demand characteristics of existing NEVI-compliant stations is crucial. However, limited access to smart meter data and few compliant stations make existing studies insufficient for NEVI research. This article presents a thorough analysis of an existing NEVI-compliant Level-3 DC charging station's power demand, located on the U.S. interstate highway in the Northern High Plains. The real 15-minute smart meter data was examined to evaluate the station's power consumption and demand characteristics across various time intervals and holidays. The station's unique location enables accurate representation of EV charging patterns for highway travel in the northern high plains throughout the year. Additionally, the study investigates the station's sustainability by assessing local solar generation potential and offers preliminary results for the future carbon market. This research provides a detailed guide on examining EV charging station power demand and consumption characteristics on the U.S. interstate highway using smart meter data, ultimately assisting the power industry in facilitating the NEVI formula program deployment.
      PubDate: THU, 06 JUL 2023 10:02:24 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Optimal Tuning of Local Voltage Control Rule of Load Tap Changers for
           Dynamic Operation of Unbalanced Distribution Networks

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      Authors: Alper Savasci;Adedoyin Inaolaji;Sumit Paudyal;
      Pages: 1322 - 1331
      Abstract: A bang-bang type control rule is typically adopted to automate the tap-changing process of on-load tap changers (OLTCs) and step voltage regulators (SVRs). The control rule is mainly characterized by a dead band parameter affecting voltage regulation performance. Due to the intermittent large-scale photovoltaic (PV) penetration, dynamic voltage fluctuations are induced along the distribution feeder, leading to frequent tap switching and equipment wear and tear. This article proposes an optimization-based dead band tuning method to reduce the number of tap switching and lengthen the economic use-life of the regulation equipment. Unlike existing works that often ignore the local controller mechanism of tap changers, this work extends the modeling efforts by formulating the dead band tuning as a distribution system optimal power flow (DOPF) problem by considering the unbalanced characteristics of multi-phase feeders. The overall DOPF is formulated as a mixed-integer linear program (MILP) to minimize the daily total number of tap switching and the amount of curtailed energy from the PV-based inverters while maintaining voltage regulation performance. Extensive numerical tests conducted on the IEEE 13-bus and IEEE 123-bus test networks suggest that the number of tap switching can further be minimized with the use of a dynamic dead band tuning strategy.
      PubDate: FRI, 08 SEP 2023 10:01:49 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Multi-Objective Operation Optimization Strategy for Integrated Community
           Energy Systems Considering Demand Side Management

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      Authors: Zilong Wang;Alian Chen;Nan Wang;Tong Liu;
      Pages: 1332 - 1344
      Abstract: The integrated community energy system (ICES) can realize the economic and environmental protection. As the critical equipment for ICES, energy router (ER) can realize the flexible transformation of different energy carriers. However, the efficiencies of the energy conversion devices in ER are usually assumed to be constant for the sake of simplicity, which may result in out-of-order operation schemes and redundant costs of ICES. In addition, the forms of multiple energy coupling of ICES are complex, and the conventional methods are difficult to coordinate the multiple energy demands. This article proposes a demand side management (DSM) method for ICES. Firstly, a dynamic ER model is built to determine the energy conversion efficiency with the variation in load rate. The energy hub model provides a mathematical representation of ER, considering energy demand and the availability of different energy sources. Then, the DR considering renewable energy output is proposed, where a real-time price strategy is established and determined by the power of load demand and generation of renewable energy. Finally, a multi-objective operation optimization strategy based on low-carbon and the economy is established. The model involves the device constraint in the process of energy production and energy transmission. The simulation results of the proposed model under different scenarios are compared. The results show that the model effectively improves the economic benefits of ICES and reduces carbon emissions, and alleviates the pressure on the energy supply.
      PubDate: MON, 11 SEP 2023 10:04:09 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Energy Management Approach to Battery Energy Storage in Unbalanced
           Distribution Networks

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      Authors: Tripti Gangwar;Narayana Prasad Padhy;Premalata Jena;
      Pages: 1345 - 1356
      Abstract: The integration of renewable energy sources (RESs) in active distribution networks (ADNs) offers numerous advantages, but it also introduces challenges such as voltage and frequency fluctuations, greater unpredictability due to RESs intermittency, and bidirectional power flow. To alleviate these undesired effects of RESs in ADNs, this work proposes energy management and optimal dispatch of battery energy storage systems (BESS). An energy management approach using optimal power flow in MATLAB as a mixed integer linear programming (MILP) problem and a rule-based method using load flow in OpenDSS is proposed to reduce the cost of operation and maintenance, losses, and voltage fluctuations in an unbalanced distribution network. Further, the BESS degradation and cycle life are considered for optimal dispatch and for determining the dispatch mode. The approach is tested on the IEEE 13-bus distribution network and a practical distribution network of a college campus. The scalability is tested using IEEE 123-bus distribution network. A comparative analysis of the results demonstrates the effectiveness in achieving the resulting benefits: operation cost saving, BESS cycle life improvement, voltage profile improvement, and loss minimization. The findings in this work highlight the potential of efficient operation of BESS to mitigate the challenges due to the proliferation of RESs in ADNs.
      PubDate: FRI, 29 SEP 2023 09:20:26 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Integrated Energy Management Scheme Considering Transportation Flexibility
           for Highway Service Zones

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      Authors: Zhaohao Ding;Yu Zhang;Dechang Yang;Liang Dai;Dawei Wang;Hongke Xu;Long Zhao;Payman Dehghanian;
      Pages: 1357 - 1368
      Abstract: The highway transportation system exhibits immense potential for adaptive functioning due to its distinctive operational attributes. This capability permits to harness more renewable energy, leading to a reduction in energy consumption costs. In this article, an integrative energy system optimization model is introduced from the standpoint of highway service zone operators. To simulate the behavior of electric vehicles on highways, an expanded network flow model is formulated considering driving, queueing, and charging actions. This model comprehensively integrates dimensions of time, space, and the state of charge of the vehicles. Consequently, the proposed model is proficient in representing the spatiotemporal and flexible operational traits inherent to electric vehicles. Through a series of numerical case studies executed on a real-world highway system, the effectiveness of the proposed model is demonstrated. These findings substantiate the potential utility and efficacy of our model in enhancing the operation optimization of energy systems within highway transportation systems.
      PubDate: FRI, 13 OCT 2023 09:16:52 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Fast State of Charge Estimation for Lithium-ion Battery Based on
           Electrochemical Impedance Spectroscopy Frequency Feature Extraction

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      Authors: Laiqiang Kong;Sidun Fang;Tao Niu;Guanhong Chen;Lijun Yang;Ruijin Liao;
      Pages: 1369 - 1379
      Abstract: A fast state of charge (SOC) estimation method is proposed based on simplified electrochemical model in this article. Firstly, the solution-phase and solid-phase lithium-ion diffusion models are stripped from the simplified electrochemical model to characterize the lithium-ion concentration. Then, based on the correlation analysis between the solution-phase lithium-ion concentration, the solid-phase surface lithium-ion stoichiometry and the obtained electrochemical impedance spectroscopy (EIS) data, key frequency features for SOC estimation are extracted through the established five feature extraction principles. Finally, the proposed SOC estimation method is expanded to consider the influences of ambient temperature. Experimental study indicates that the integration of lithium-ion diffusion process can significantly improve the accuracy of SOC estimation and reduce the computational time compared with the traditional broadband domain method and the fractional-order equivalent circuit model (FOECM).
      PubDate: MON, 16 OCT 2023 09:18:15 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Hierarchical Power Management of Shipboard Hybrid Energy Storage System
           Under Multiple Pulse Loads

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      Authors: Yingbing Luo;Sidun Fang;Tao Niu;Ailong Fan;Ruijin Liao;
      Pages: 1380 - 1395
      Abstract: All-electric ships face multiple onboard pulse loads, including propulsion fluctuations resulting from uncertain navigation conditions, and the power demands of radar or weapon systems. In this paper, a large-scale hybrid energy storage system (HESS) is utilized to provide multi-timescale flexibility to coordinate the main engines to mitigate the impacts of those pulse loads, and a hierarchical power management method is proposed by two steps: the first is to quantify multiple pulse loads and propose a “rolling charging/discharging” strategy to mitigate the pulses; the second considers the power characterization of the battery and proposes a model-free adaptive learning control to reduce unnecessary charging/discharging cycles of HESS and adaptively deal with the impact of navigation uncertainties on the battery. The proposed method is proved by three case studies, and the results show: 1) compared with the case of the single main engine power supply, the proposed “rolling charging/discharging” strategy can reduce the deviation of DC voltage by 84.5%; 2) compared with conventional four methods, the proposed strategy can reduce the internal energy flow and the power tracking error in HESS and the power fluctuation of battery by 75.65%, 95.38%, and 22.9% at most, respectively; and 3) adaptively ensure that the safety operation of the battery under uncertain conditions.
      PubDate: THU, 19 OCT 2023 09:17:10 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Enhancing One-Day-Ahead Probabilistic Solar Power Forecast With a Hybrid
           Transformer-LUBE Model and Missing Data Imputation

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      Authors: Quoc-Thang Phan;Yuan-Kang Wu;Quoc-Dung Phan;
      Pages: 1396 - 1408
      Abstract: Forecasting solar photovoltaic (PV) power generation has become important due to solar power's chaotic and intermittent nature. With the development of artificial intelligence (AI) techniques, particularly deep learning algorithms, has proven to be very powerful for renewable power forecasts. This study aims to develop a probabilistic forecasting approach, leveraging the Transformer-Lower Upper Bound Estimation (Transformer-LUBE) hybrid model, enhanced by data processing techniques, for one-day-ahead PV power generation forecasts. This involves integrating an effective imputation technique, modifying the Transformer architecture, and employing a combined post-processing approach. In the pre-processing stage, missing data are imputed using XGBoost in combination with predictive mean matching (PMM) and bootstrapping. The Pearson Correlation Coefficient is then utilized to compute correlations between input features. Unlike the original Transformer architecture, the proposed model incorporates additional normalization and dropout layers between blocks, as well as multi-head attention mechanisms. Finally, a post-processing strategy is implemented based on daily numerical fitting curves along with Gated Recurrent Unit (GRU) to correct residual error biases. The framework is trained using historical measurement data from ten solar farms in Taiwan, as well as Numerical Weather Predictions (NWPs) data from the Taiwan Central Weather Bureau (CWB). The accuracy of the proposed model is evaluated in comparison to other AI models, including Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), GRU, and XGBoost. Through comprehensive experimentation, the proposed framework demonstrates superior accuracy and reliability.
      PubDate: THU, 19 OCT 2023 09:17:10 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Overview of Day-Ahead Solar Power Forecasts Based on Weather
           Classifications and a Case Study in Taiwan

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      Authors: Yuan-Kang Wu;Quoc-Thang Phan;You-Jing Zhong;
      Pages: 1409 - 1423
      Abstract: Solar power forecasting is essential for optimizing energy management and ensuring stable grid operations. Accurately forecasting solar irradiance is a key factor to improve solar power forecasts because of a strong relationship between solar power generation and solar irradiance. However, the accuracy of solar irradiance forecasting is affected largely by the limits inherent in Numerical Weather Prediction (NWP). Thus, there exists a notable opportunity to improve the forecast beyond NWP by using data processing technologies. Among them, one is based on the classification of weather patterns. This paper aims to propose several PV power forecasting methods based on weather patterns, and to develop appropriate models for each classification. The proposed five clustering methods include the use of K-Means or SOM algorithm, a time-based classification, an amplitude threshold-based classification using PSO and GWO algorithms, and a season-based classification. Moreover, three up-to-date AI models including XGBoost, GRU, and Transformer were then applied to predict one-day-ahead PV power. Through a systematic experimentation and comparative analysis, the developed forecasting method considering weather classifications with Transformer training model achieves the highest forecasting accuracy on both deterministic and probabilistic forecasts. Furthermore, the forecasting results also reveal the potential advantages for different clustering methods. The time-based and season-based classification models can capture specific climate characteristics of different time periods and seasons, respectively.
      PubDate: TUE, 24 OCT 2023 09:18:36 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Modified Protection Algorithm for a Non-Homogeneous Shunt-Compensated
           Transmission Line Against Phase-to-Ground Fault

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      Authors: Abhishri Jani;Vijay H. Makwana;
      Pages: 1424 - 1432
      Abstract: Traditional digital distance relaying scheme is used to protect the transmission lines against various abnormal conditions/faults. In this article, the authors have discussed the adverse effects of fault and system parameters, such as fault resistance, fault location, power transfer angle etc., on the performance of the protection scheme. Further, a PV integrated microgrid is considered at one end of a doubly-fed transmission line network to analyze the effect of weak source, thereby, incorporating the concept of non-homogeneity in the system. A modified protection algorithm is proposed to mitigate the effect of all the aforementioned variations on the protection of shunt-compensated transmission line. This protection algorithm is based on the mathematical analysis of the sequence components of voltage, current and impedance of the network components. An equivalent impedance vector for each of the above-stated fault and system parameters is obtained and the relationship between these vectors is represented in vectorial form. With the help of this vector diagram and the mathematical analysis, the actual impedance of faulted part of the line is calculated. Since the algorithm is derived mathematically, it is simple to understand and user-friendly. A negligible error is observed while simulating the modified protection algorithm considering all the severe variations in fault and system parameters. Modified DFT algorithm is used to improve the transient response and operating time of the relaying algorithm. MATLAB/Simulink software is used to verify the proposed algorithm using non-homogeneous power system.
      PubDate: TUE, 19 SEP 2023 10:03:12 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Does Choice of Power Flow Representation Matter in Transmission Expansion
           Optimization' A Quantitative Comparison for a Large-Scale Test System

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      Authors: Mahdi Mehrtash;Benjamin F. Hobbs;Reza Mahroo;Yankai Cao;
      Pages: 1433 - 1441
      Abstract: Power transmission network reinforcements must be carefully evaluated to ensure economic, secure, and reliable delivery of electricity. Transmission expansion planning (TEP) models, which seek to optimize the timing, location, and voltages of new transmission lines, can be useful for this task. In general, such models can be mixed-integer nonconvex models due to the discrete nature of investments and AC power flow representations. The original nonconvex TEP model (i.e., ACTEP) is approximated as a linear model (i.e., DCTEP) in most studies. However, the accuracy of this TEP approximation has not been quantified for large-scale power systems. In this article, we first propose a large-scale test system for ACTEP studies, which addresses drawbacks of existing test systems. An ACTEP global solver (i.e., Global-TEP) is used to obtain global solutions of the proposed test system with a guaranteed optimality gap, which allows it to serve as a benchmark for future ACTEP studies. Then, differences among solutions of four TEP models (i.e., DCTEP, local solution of ACTEP, global solution of ACTEP, and global solution of ACTEP with reactive power compensator expansion) are quantified. To our knowledge, this is the first quantitative comparison of DCTEP vs. ACTEP global solutions on a large-scale system. Since a significant difference is observed between the DCTEP and ACTEP solutions, and since the DCTEP solution's performance is significantly worse when verified by an AC load flow model, considering the exact AC power flow representations in TEP studies is recommended.
      PubDate: TUE, 19 SEP 2023 10:03:12 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Enhancing Power Grid Resilience Against Typhoon Disasters by Coordinated
           Scheduling of Source-Network-Load

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      Authors: Heng Zhang;Shenxi Zhang;Fangping Chen;Zheng Li;Haozhong Cheng;Gang Li;Xiaohu Zhang;
      Pages: 1442 - 1453
      Abstract: To enhance the resilience of power grids against typhoon disasters, this study proposes a novel preventive scheduling method by coordinating source, network, and load resources. An evaluation index for unexpected load shedding that considers the importance of load is provided on the basis of the utility function and employed as the objective function. Moreover, the piecewise function based objective function is transformed into a mixed-integer linear formulation by introducing auxiliary variables with clear physical meanings. The startup and shutdown arrangements of units and the optimal scheduling of their outputs, as well as the opening and closing of line switches, for protecting the power supply of important loads and various demand-side management measures are comprehensively modeled. In response to the difficulty in solving the problem caused by numerous factors considered in the model, an identification method for variable and constraint reduction by narrowing the range of switchable lines is proposed to verify the effectiveness of the switchable lines in optimal transmission switching (OTS) in reducing the congestion caused by typhoon disasters. The proposed method is applied to the modified IEEE two-area system and the IEEE-118 system. Results indicate that the utility function based collaborative preventive scheduling method can effectively reduce the loss of important loads during disasters, without excessively cutting off other loads, compared with the widely used load shedding based method. Furthermore, the model dimensionality reduction method based on the effectiveness identification of switchable lines can greatly improve the solving efficiency with on decrease in the accuracy.
      PubDate: MON, 25 SEP 2023 09:20:14 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Volt-Var Optimization With Power Management of Plug-In Electric Vehicles
           for Conservation Voltage Reduction in Distribution Systems

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      Authors: Darwin A. Quijano;Antonio Padilha-Feltrin;João P. S. Catalão;
      Pages: 1454 - 1462
      Abstract: This article addresses the problem of Volt-Var optimization for conservation voltage reduction (CVR) implementation in medium voltage electric distribution systems (EDS) with high penetration of renewable energy sources (RES)-based distributed generation (DG) and plug-in electric vehicles (EVs). The proposed strategy seeks to coordinate the power dispatch of aggregated electric vehicles (EVs) for EDS voltage regulation taking into account technical characteristics and the driving patterns of individual EVs. Active and reactive V2G capabilities of EV chargers are harnessed to enhance the capacity for voltage regulation and energy savings. The strategy is for the day-ahead operation scheduling, where decisions are made based on predictions of RES-based DG power production, conventional load consumption and EV driving patterns. Forecast errors are taken into account through a two-stage stochastic programming formulation, where probability density functions are used to describe the uncertainties of predicted parameters. Simulations were carried out on a 33-bus test system and results showed energy savings of up to 4.14% when EVs participate in voltage control.
      PubDate: MON, 25 SEP 2023 09:20:14 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Semi-Definite Programming Based Scalable and Accurate Optimal Power Flow
           Models for Radial Distribution Networks

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      Authors: Md Shamim Hasan;Md Mahmud-Ul-Tarik Chowdhury;Biswajit Dipan Biswas;Sukumar Kamalasadan;
      Pages: 1463 - 1475
      Abstract: With high integration of distributed energy resources (DERs), modern distribution networks are subject to optimal power flow (OPF) analysis. Conventional non-linear and linear OPF models suffer from either infeasibility or inaccuracy for large networks, and global optimality is not guaranteed. Addressing computational infeasibility and non-convexity for DERs integrated distribution networks, this article presents a novel approach for OPF analysis employing semi-definite programming (SDP). For the proposed SDP-OPF model, network power flow relations utilize a bus injection model (BIM) for single-phase networks and a branch flow model (BFM) for multi-phased unbalanced power distribution networks. The exactness and the global optimality of the proposed SDP-OPF model are illustrated in this article. The proposed models' performance is evaluated in multiple standard power distribution test cases with a wide range of DER integration. The simulation results are compared with a nonlinear programming (NLP) based and a second order cone programming (SOCP) based OPF models. The comparison and the result analysis demonstrate that the proposed approach yields a more robust solution with improved convergence and accuracy.
      PubDate: THU, 28 SEP 2023 09:17:21 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Topology Error Monitoring Using Bad Data Detection Methods

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      Authors: Ken Crawford;Mesut E. Baran;
      Pages: 1476 - 1483
      Abstract: For real-time monitoring of distribution systems, distribution system state estimation (DSSE) methods have been developed. For accurate DSSE results, an accurate system model is needed. However, topology of a distribution network changes due to various reasons and some changes may not be monitored or known to the control center. This leads to an incorrect model used for the DSSE and thus causes incorrect estimation results. The main contributions of this article includes development of a topology monitoring scheme using bad data detection (BDD) methods in the presence of the most common topology errors in practice, including capacitor bank failure and load balancing. Additionally, common measurement schemes are investigated to determine how a measurement scheme can be used in order to improve topology error detection. Test results using a sample IEEE distribution feeder have been provided to illustrate the the effectiveness of the proposed scheme.
      PubDate: FRI, 29 SEP 2023 09:20:26 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Impedance Modeling With Stability Boundaries for Constant Power Load
           During Line Failure

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      Authors: Utkal Ranjan Muduli;Mohamed Shawky El Moursi;Iraklis P. Nikolakakos;Khalifa Al Hosani;Sayed Abdelaziz Mohammad;Tareg Ghaoud;
      Pages: 1484 - 1496
      Abstract: Harbor cranes particularly use induction motors (IM) as the main prime mover, which are powered by the grid through the machine side converter (MSC) followed by a grid side converter (GSC). To supply power to multiple cranes in parallel, double-circuit lines are utilized. Failure of a single feeder causes voltage instability in the load bus. To analyze the voltage stability on the load bus, this article proposes a comprehensive model of the GSC while simplifying the MSC as constant power loads (CPL). When used to describe the CPL behavior of the connected IM load, the proposed modeling shows how input admittance behaves as a negative incremental, growing voltage instability on the load bus. This study uses Nyquist-based stability analyzes to address the voltage stability issue caused by a double-circuit line failure and a negative incremental input admittance. The feasibility of creating a phase-locked loop (PLL) for such grid disturbances is investigated. The possibility of installing a static VAR compensator (SVC) with a battery energy storage system (BESS) on the load bus is explored if there is no equilibrium point in the $P_{e}$ - $\delta$ curves during line failure.
      PubDate: FRI, 29 SEP 2023 09:20:26 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Wind Turbine Fault Detection and Estimation Based On Nonlinear Observer

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      Authors: Ichrak Eben Zaid;Moez Boussada;Ahmed Said Nouri;
      Pages: 1497 - 1507
      Abstract: This article deals with the fault detection strategy used to ensure wind turbine reliability. The proposed approach is based on an Unknown Input High Gain Observer (UIHGO) for a class of nonlinear systems subject to actuator and sensor faults. Compared to some usually used algorithms, this method presents the benefits of reduced calculation time as well as development effort and accuracy, which makes it useful for online implementation even for fast processes. Used for linear systems, such approaches demonstrated interesting performances and results. The problem becomes harder for nonlinear systems, where models are characterized by complex and coupled behaviors. Moreover, faults have to be detected as early as possible to avoid catastrophic and irreversible damage. Applied to a simulated wind turbine plant to reconstruct not only the full system state but also the faults altering the electromechanical torque subpart and the generator speed signal, the results confirmed the accuracy and time convergence performances of the proposed observer, which make it an interesting candidate to overcome fault detection for nonlinear systems.
      PubDate: MON, 02 OCT 2023 09:18:57 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Integrating Solar Resources and Topology Estimation Modules in Industrial
           ADMS Environment

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      Authors: Surendra Bajagain;Chuan Qin;Sanjeev Pannala;Anurag Srivastava;Anamika Dubey;
      Pages: 1508 - 1518
      Abstract: In contrast with traditional utility monitoring and operational tools, advanced distribution management systems (ADMS) provide modern operational features to monitor, secure and operate the distribution system in an integrated manner. Large-scale adoption of ADMS at utilities is in the early stages since advanced applications within ADMS environments are still evolving. The topology estimation module is one of the important and challenging ADMS applications with enhanced automation. This article integrates the optimization-based topology estimation module with the load/photovoltaics (PV) estimation module. Validation of the feeder connectivity information is the major challenge faced during the integration process. The statistical analysis of the error of the load/PV estimation module shows that the error does not follow the Gaussian distribution. To accurately capture the uncertainty in the error of the load/PV estimation module, the error is modeled with the Gaussian mixture model (GMM). The study using the actual utility feeder data and the ADMS platform shows that in an integrated operation of the load/PV estimation module and topology estimation module, the accuracy of the topology estimation module is improved when the estimation error of the load/PV estimation module is modeled with GMM. The methodology outlined in this article serves as the proof-of-concept and framework for integration and validation of advanced applications such as load/PV estimation and topology estimation modules in the ADMS environment.
      PubDate: WED, 04 OCT 2023 09:19:13 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Grid-Interactive Smooth Transition Control of Wind-Solar-DG Based
           Microgrid at Unpredictable Weather Conditions

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      Authors: Sambasivaiah Puchalapalli;Bhim Singh;Souvik Das;
      Pages: 1519 - 1529
      Abstract: This article presents the grid interactive wind-solar-diesel generator (DG) based microgrid (MG) at unpredictable weather conditions with improved reliability of power. With enhanced reliability, loads are powered continuously during both on-grid and off-grid modes. In view of sensitive loads, DG is used in the system on grounds of its dispatchability, which is lacking in the wind-solar power generation. However, DG is controlled to consume minimum fuel during its operation. The wind power is captured by using a doubly fed induction generator (DFIG). Moreover, a battery bank is connected in the system for energy storage and to deliver when its need arises. Modified controls are presented for converter on rotor side (CRS) and converter on load side of DFIG to make MG flexible for on/off-grid operations and for smooth connection/disconnection of DG. An adaptive step change incremental conductance based maximum power point tracking (MPPT) technique is utilized for acquiring peak power from solar photovoltaic (PV) array. Moreover, a modified adaptive step change based perturb and observe wind MPPT strategy is incorporated in control of CRS for improved power capturing as compared to conventional fixed step methods. Simulated results are presented to evidence MG performance along with a comparison of wind turbine efficiency. Moreover, an experimental test bench is built to evidence dynamic and steady state performance of MG at various operating scenarios i.e., at varying winds and varying solar irradiances, during on/off-grid modes and smooth connection/disconnection of DG, and at change in loads.
      PubDate: FRI, 06 OCT 2023 09:17:52 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Fault-Isolation Scheme for Flexible DC Distribution Networks With Multiple
           Types of Converters

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      Authors: Zhihui Dai;Yiran Li;Shanshan Liu;Jian Zhao;Tong Wu;Xueyan Liu;
      Pages: 1530 - 1542
      Abstract: Complete fault-isolation schemes for flexible DC distribution networks with multiple types of converters are rare. In this work, a fault-isolation scheme based on the new-type multi-port DC circuit breaker (MP-DCCB) and improved converters (modular multi-level converters, voltage source converters, and DC transformers) with current-limiting and fault-isolation capability is proposed. The fault currents are limited by the thyristor-based fault current limiter. Thereafter, multi-type faults are isolated by the coordination of MP-DCCB and improved converters. The working principle of the new scheme is analyzed by establishing equivalent models, and its validity under different scenarios is verified by simulations. Moreover, its advantages are demonstrated by comparing its performance with other typical schemes in terms of economy and functionality.
      PubDate: MON, 09 OCT 2023 09:18:58 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Influence of Ageing on Properties of Insulating Oil and Life Estimation of
           In-Service Transformer and Reactors: A Latent Variable Approach

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      Authors: Devaprasad Paul;Arup Kumar Goswami;
      Pages: 1543 - 1552
      Abstract: This article aims at analysing the degradation properties of oil parameters such as breakdown voltage (BDV), interfacial tension (IFT), resistivity, acidity, moisture, dielectric loss tangent, and total gas content due to ageing of transformer and reactors. For ensuring long term reliability of transformer and reactor it is necessary to ascertain the degradation characteristics of the insulating oil along with its impact on healthiness of the equipment. The article investigates the correlation among different aged oil parameters and finds the significance of individual oil characteristic and dissolved gases for evaluating the condition of oil filled equipment. Thereafter, factor analysis is performed for identifying any interdependency between various oil parameters. Subsequently, structural equation modelling is carried out for evaluating the contribution of common factors on total ageing of the transformer and reactors. Finally, the ageing health index has been calculated and based on that the residual life estimation of equipment is done. The data considered comprises of actual oil test data of 442 samples collected from 60 numbers of in-service transformers and reactors of various age groups. The outcome of this study can be used for monitoring the deteriorating characteristics of the oil filled equipment as well as for determining the residual life of in-service transformers and reactors along with planning of maintenance strategies.
      PubDate: WED, 11 OCT 2023 09:18:00 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Bivariate Modeling of Normalized Energy Intensity of Oil and Paper for
           Determining the Health Index of In-Service Transformers and Reactors

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      Authors: Devaprasad Paul;Arup Kumar Goswami;
      Pages: 1553 - 1563
      Abstract: This article aims at developing a copula model for investigating the dependence structure between normalized energy intensity of oil $(\mathbf{NE}{\mathbf{I}}_{\mathbf{oil}})$ and normalized energy intensity of paper ($\mathbf{NE}{\mathbf{I}}_{\mathbf{paper}}).$ The normalized energy index is a quantity that is directly related to the energy dissipated during a fault inside an oil filled transformer and reactor. The $\mathbf{NE}{\mathbf{I}}_{\mathbf{oil}}$ and $\mathbf{NE}{\mathbf{I}}_{\mathbf{paper}}$ are derived from real time dissolved gas analysis data of in-service transformer and reactors. Gumbel copula has been used for evaluating the conditional probabilities between the parameters. Results of the copula model indicate that for an increment of 0.5 kJ/kL in $\mathbf{NE}{\mathbf{I}}_{\mathbf{oil}}$ there is an increment in $\mathbf{NE}{\mathbf{I}}_{\mathbf{paper}}$ between 1.0 and 2.2 kJ/kL. It demonstrates the importance of considering $\mathbf{NE}{\mathbf{I}}_{\mathbf{paper}}$ in addition to $\mathbf{NE}{\mathbf{I}}_{\mathbf{oil}}$ for assessing the fault severity and evaluating the internal condition of liquid and solid insulation of transformer and reactor. Subsequently, the health index of transformers and reactors considering oil parameters, $\mathbf{NE}{\mathbf{I}}_{\mathbf{oil}}$ and $\mathbf{NE}{\mathbf{I}}_{\mathbf{paper}}$ have been evaluated thus making it an unique nature of study. Additionally, a range of values of $\mathbf{NE}{\mathbf{I}}_{\mathbf{oil}}$ and $\mathbf{NE}{\mathbf{I}}_{\mathbf{paper}}$ has been determined which can be used directly for future study. The study undertaken will help in monitoring, maintenance, and conditioning assessment of the equipment based on NEI values, thereby saving unprecedented failure of in-service transformers and reactors.
      PubDate: WED, 11 OCT 2023 09:18:00 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Coordinated Energy Dispatch and Flexibility Support for Microgrid Cluster
           Using Rule-Based Stackelberg Gaming Approach

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      Authors: Zhanpeng Chen;Feilong Fan;Nengling Tai;Yan Hu;Ran Li;
      Pages: 1564 - 1575
      Abstract: It is significant to explore the flexible regulation ability of microgrids for accepting distributed renewable energy. This article proposes a coordinated energy dispatch and flexibility support method for microgrids. Firstly, set up the aggregator to combine microgrids into the microgrid cluster. Then, the Stackelberg game model is constructed to analyze the interaction between microgrids and the microgrid cluster. As the leader, the aggregator guides microgrids to participate in demand-side response by using internal electricity price incentives. As followers, microgrids change their demand according to electricity prices and provide flexible peak-shaving services. By optimizing the electricity price, all participants in the game can obtain higher returns. Moreover, to improve the market competitiveness of flexibility services provided by the microgrid cluster, a real-time flexibility dispatching model is established, thereby reducing the main grid flexibility dispatch cost. Numerical results demonstrate that the proposed method can effectively enhance the system's flexibility and economy. Compared to directly trading with the superior power grid, the revenue of the microgrid cluster has increased by 2.37%, and the flexible supply capacity has improved by 11.88%.
      PubDate: THU, 12 OCT 2023 09:16:33 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Optimal Selection of Voltage Controlling Parameter in Uncertain Active
           Distribution Network

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      Authors: Digamber Kumar;Bibhu Prasad Padhy;
      Pages: 1576 - 1588
      Abstract: Nowadays, converter base generation (CBG) and charging infrastructure penetration are increasing rapidly in the distribution system. Thus, maintaining the voltage profile of the distribution system becomes a challenging task due to the uncertain characteristics of CBG, the number of EVs arriving at the charging stations (CS) and the power demand by the load. Therefore, in this article, the voltage profile is improved by choosing optimal voltage-controlling parameters. This is achieved through solving multi-objective optimal power flow (OPF) problem in a distribution system with CBG, like solar and wind. Further, the Modified Jaya (M-Jaya) algorithm has been used to solve the optimization problem by converting multi-objectives, such as minimization of line losses, minimization of voltage deviation and maximization of CBG output power, to a single objective function. Moreover, the state-based probabilistic model has been used to incorporate the stochastic characteristics of output from CBG, the number of EVs arriving at the CS and power demand by the load in the OPF. The numerical test of the multi-objective optimal power flow with the proposed state-based probabilistic model has been done on enhanced IEEE-33 and IEEE-123 unbalanced test system by determining the optimal rating of voltage-controlling parameters for the 24 h (h) time period.
      PubDate: MON, 16 OCT 2023 09:18:15 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Coordinated Robust Damping Control for Hybrid SVC/SSSC to Enhance Power
           System Stability in Large-Scale Systems

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      Authors: Suraj Ankush Dahat;Ashwin Dhabale;
      Pages: 1589 - 1598
      Abstract: The restoration of stability is major problem in power transmission system after the disturbance. Flexible AC transmission system (FACTS) devices have the ability to restore the stability of the system by manipulating the transmission parameters. The combination of FACTS devices is more effective than single device used alone. This article investigates a coordinated control strategy involving static VAR compensator (SVC) and static synchronous series compensator (SSSC). The SSSC is used to lower the line's equivalent impedance and improve its active power transfer capabilities. To maintain bus voltage magnitude, a SVC is used for shunt compensation. Utilizing identical signal input tracking enables the operation of a device depending on the compensation provided by the other device. The efficacy of the proposed scheme is demonstrated by applying it to a tie line of two area 4-machine 11-bus Kundur test system and observing the system variables after a major fault is created on another tie line. The improvement achieved is highlighted by comparing the behavior with that of the uncompensated and conventionally compensated system. The simulation study is carried out in MATLAB Simulink which further supported by the real time simulation in Opal RT digital simulator. Also, cost function analysis shows that the proposed scheme is cost effective compared to other conventional schemes.
      PubDate: TUE, 17 OCT 2023 09:17:39 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • A Complete Electrical System Study for a Refinery With Major Expansion

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      Authors: JJ Dai;
      Pages: 1599 - 1610
      Abstract: A full electrical system study for a large refinery with major expansion is reported. The expansion added two new gas turbine generators (GTG) as well as one new steam turbine generator (STG) to the system. A gas-insulated switchgear (GIS) lineup was installed at the 22 kV main substation with a new current limiting reactor to tie the main buses. Four of the substations are new as part of the expansion to increase the total number of substations to fourteen. Due to the new generators, a complete system study to size equipment, adjust protection settings, verify operating conditions and ensure system stability was carried out. The system study scope includes load flow, short circuit, protection and coordination, motor starting, and transient stability. The project lasted and covered the entire construction stages from For Review (FR) and For Design (FD) to For Construction (FC). The detailed system study helped the construction contractor and refinery owners to validate system design, confirm operation procedures and finalize protection schemes under both normal and abnormal conditions. Further, this paper shares experiences gained from performing and managing a complete system study project for an industrial facility in after front-end engineering design (FEED) phase in terms of validating system models, selecting study scenarios, leveraging computer software features, analyzing study results and proposing recommendations.
      PubDate: THU, 19 OCT 2023 09:17:10 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Risk Analysis of Transactive Energy Retail Markets

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      Authors: David Toquica;Fatima Amara;Roland Malhamé;Kodjo Agbossou;Nilson Henao;Juan C. Oviedo;Luis Rueda;
      Pages: 1611 - 1621
      Abstract: New grid management schemes have created exciting opportunities for end customers to maximize their utility by becoming active participants. In particular, Transactive Energy Systems (TES) allow customers to cooperate and negotiate in energy markets, increasing social welfare. These interactions also reduce demand-side uncertainties and simplify grid balancing at different levels. In TES, it is beneficial to employ forward contracts because they establish conditions for future energy supply, allowing grid maintainers to plan a cost-effective operation. Thus, end customers interact in local retail markets in advance to agree on service conditions that fulfill their needs. This paper presents a comprehensive analysis of the risks involved in those forward contracts with the aim of providing valuable information to participants. The TES environment modifies the typical risks of electricity contracts due to the information exchange in the negotiation and execution stages. Indeed, reliable data and realistic forecasting assumptions become a primary concern for each participant since they constitute the main threat of contract defaulting. Risk management strategies are presented in bow-tie and Ishikawa diagrams to elicit the decisions for market participants. Case study results demonstrate that forecasting errors impact the conditional value at risk of the contracts, in proportion to the demand uncertainty.
      PubDate: WED, 25 OCT 2023 09:16:54 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Cyber Anomaly-Aware Distributed Voltage Control With Active Power
           Curtailment and DERs

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      Authors: Partha S. Sarker;Md. Fazley Rafy;Anurag K. Srivastava;R. K. Singh;
      Pages: 1622 - 1633
      Abstract: Operations of power distribution systems with Distributed Energy Resources (DERs) can be managed in scalable manner with advanced distributed control algorithms. Distributed algorithms utilizing digital controller also bring cyber vulnerabilities. In this work, a converter-inverter topology that can utilize a communication network and a distributed feedback-based Volt-Watt controller has been developed. Circuit topology of the converter-inverter and DER is verified with both PSIM simulation software and a laboratory prototype shown. The paper presents multiple simulated cyber attack scenarios exploiting vulnerabilities to test the capability of the developed distributed control approach. Finally, a multivariate LSTM-autoencoder-based anomaly detection-mitigation application has been developed to minimize the impact of cyber attacks on distributed controller operations. To validate the developed algorithms, a Cyber-Physical System (CPS) test-bed has been developed, which uses OpenDSS for power system simulation, Mininet for communication network emulation, and integrates applications using Python. The test-bed has been designed to simulate comprehensive distributed operations with various use cases, including attack surfaces, distributed control, and detection-mitigation applications. Our developed approaches have been validated using a modified 123-bus unbalanced distribution network with DERs. The results clearly show that our proposed converter-inverter topology for DER integration, voltage control application, and anomaly detection-mitigation application can significantly improve the efficiency, performance, and security of distribution systems that rely on DERs.
      PubDate: TUE, 31 OCT 2023 09:17:01 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • An Integrated Assessment of a G3 GMD Event on Large-Scale Power Grids:
           From Magnetometer Data to Geomagnetically Induced Current Analysis

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      Authors: Pooria Dehghanian;Anna Zhang;Rida Fatima;Jonathan Snodgrass;Adam B. Birchfield;Katherine R. Davis;Thomas J. Overbye;
      Pages: 1634 - 1644
      Abstract: Solar activity can cause geomagnetic disturbances (GMDs) that give rise to geomagnetically induced currents (GICs) which may compromise the reliability of the electric grid.In order to build more reliable models representing GMD interactions with the power grid, the power system's detailed electrical model must be considered along with fluctuations in the earth’s magnetic and induced surface electric fields. This study investigates the impact of incorporating spatially varying magnetic fields into surface electric field models on GMD risk metrics. A spatially independent magnetic field model and a spatially varying model are compared through simulations. To perform this analysis, the earth’s magnetic field disturbances are transformed into surface electric fields using respective one-dimensional Earth conductivity models. Then, the modeling impact of these electric fields is studied using a 2,000-bus grid for Texas and a 25,000-bus grid for the northeast and mid-Atlantic regions of the United States. Simulation results reveal that the inclusion of spatially varying magnetic fields results in considerable differences in GMD risk metrics, highlighting the importance of accounting for spatial variability when assessing GMD risks in the power system.
      PubDate: TUE, 31 OCT 2023 09:17:01 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • An Experimental Methodology for Modeling Surge Protective Devices: An
           Application to DC SPDs for Electric Vehicle Charging Stations

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      Authors: Thomas E. Tsovilis;Alexandros Y. Hadjicostas;Evangelos T. Staikos;Georgios D. Peppas;
      Pages: 1645 - 1655
      Abstract: This work introduces an experimental methodology for time-domain modeling of low-voltage surge protective devices (SPDs), accounting for their sparkover performance as well as their resistive, inductive, and capacitive behavior. The modeling procedure is demonstrated through an application to a combination type SPD connected to the DC side of electric vehicle charging stations. An equivalent circuit model is developed based on experimental records acquired from applied voltages and currents of a wide frequency range and energy content. The developed lumped-circuit model yields results in very good agreement with experimental data regarding sparkover voltage, residual voltage, and energy absorption of SPDs, as illustrated through ATP-EMTP simulations. The proposed methodology can be an effective tool for surge protection and insulation coordination studies.
      PubDate: THU, 07 SEP 2023 10:02:20 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Retrofitting of an Air Handling Unit by a Two-Stage Electrostatic
           Precipitator

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      Authors: Yeawan Lee;Ye-Sle Kim;Haneol Lee;Yewon Park;Gwangtaek Lee;So-Hee An;Bangwoo Han;Yong-Jin Kim;Hak-Joon Kim;
      Pages: 1656 - 1664
      Abstract: A two-stage electrostatic precipitator (ESP) was developed using carbon brush ionizers and lightweight plastic electrodes to be used in an air handling unit (AHU). In a pilot study, the developed ESP emitted near-zero ozone (
      PubDate: FRI, 22 SEP 2023 09:18:16 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Damping of Inter-Area Oscillations With Frequency Regulation in Power
           Systems Considering High Penetration of Renewable Energy Sources

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      Authors: Abhineet Prakash;Mohamed Shawky El Moursi;S. K. Parida;Kundan Kumar;Ehab F. El-Saadany;
      Pages: 1665 - 1679
      Abstract: Due to high penetration of renewable energy sources, inter-area oscillations (IAOs) have become serious concern for power system stability. Hence, a wide-area damping controller (WADC) strategy is proposed for thyristor-controlled series compensator (TCSC) device to effectively damp IAOs. The feedback signals for the WADC design are selected by the modal sparse linear quadratic regulator (MSLQR) method, which are sole signals that modulate simple gains to achieve the desired damping performance. Moreover, the multi-model framework approach is adopted to ensure optimal damping corresponding to any uncertainties such as changing operating scenarios and time latency in feedback signals. However, the proposed primary control does not provide frequency regulation; hence, a secondary control based on the switched integral controller is applied in addition to primary damping control to further maintain the frequency at the steady-state level. Performance of suggested strategy is evaluated and verified on IEEE 4-machine, 11-bus system and 16-machine, 68-bus system. A comprehensive analysis shows significant improvement in the damping performance of concerned modes, leaving the local modes almost unaffected while maintaining the frequency at the prescribed steady-state level.
      PubDate: TUE, 05 SEP 2023 10:03:19 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Advancement of Active Disturbance Rejection Control and Its Applications
           in Power Electronics

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      Authors: Liangcai Xu;Shengrong Zhuo;Jianxing Liu;Shudan Jin;Yigeng Huangfu;Fei Gao;
      Pages: 1680 - 1694
      Abstract: The powerful control ability of the active disturbance rejection control (ADRC) method has attracted much attention from both the academic and industrial communities. This method successfully inherits the advantages of the conventional proportional integration (PI) control method, such as error-driven way, simple structure, and low design complexity. In addition, it also absorbs the observer technique from modern control theory. All these factors make the ADRC method show a big potential to be widely adopted in practical industrial applications. To facilitate this development trend, in this work, some advancements of ADRC are discussed in detail, and three typical applications in the power electronics field are briefly introduced, such that the engineers can have a more intuitive understanding of this method and the academics could recognize some topics that still need to be further researched.
      PubDate: THU, 07 SEP 2023 10:02:20 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • BSL: Navigation Method Considering Blind Spots Based on ROS Navigation
           Stack and Blind Spots Layer for Mobile Robot

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      Authors: Masato Kobayashi;Naoki Motoi;
      Pages: 1695 - 1704
      Abstract: This article proposes a navigation method considering blind spots based on the robot operating system (ROS) navigation stack and blind spots layer (BSL) for a wheeled mobile robot. In this article, environmental information is recognized using a laser range finder (LRF) and RGB-D cameras. Blind spots occur when corners or obstacles are present in the environment, and may lead to collisions if a human or object moves toward the robot from these blind spots. To prevent such collisions, this article proposes a navigation method considering blind spots based on the local cost map layer of the BSL for the wheeled mobile robot. Blind spots are estimated by utilizing environmental data collected through RGB-D cameras. The navigation method that takes these blind spots into account is achieved through the implementation of the BSL and a local path planning method that employs an enhanced cost function of dynamic window approach. The effectiveness of the proposed method was further demonstrated through simulations and experiments.
      PubDate: THU, 07 SEP 2023 10:02:20 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Hybrid Sensor Fault Tolerant Control of Low Voltage DC Microgrid

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      Authors: M. V. Satya Sai Chandra;Sankarsan Mohapatro;
      Pages: 1705 - 1715
      Abstract: Low voltage DC (LVDC) microgrids have recently gained popularity. In applications such as rural electrification, data center power systems, and satellite microgrids stand-alone LVDC microgrids have proven to be extremely beneficial. In the case of standalone LVDC microgrids, voltage control and energy management are crucial. In such standalone and safety-critical systems, sensor faults are especially important to address. Therefore, we present a hybrid sensor fault tolerant control (HSFTC) approach with redundancy features at the software and hardware levels. To address voltage sensor failures, an analytical redundancy component employs a sliding mode observer in conjunction with adaptive passivity-based control. To overcome battery current sensor failures, a double modular hardware redundancy component is included. Both MATLAB simulations and hardware experiments on the microgrid testbed are used to verify the performance of this HSFTC in a variety of scenarios involving sensor malfunctions and load disturbances. We observe that the suggested HSFTC can address sensor faults and load disturbances simultaneously. The effectiveness of our control approach in dealing with sensor malfunctions is evaluated in comparison to reference control strategies.
      PubDate: THU, 14 SEP 2023 10:01:50 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Modeling and Robust Optimization of Commercial Air-Water HVAC System

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      Authors: Samy Faddel;
      Pages: 1716 - 1724
      Abstract: Heating, Ventilation and Air Conditioning (HVAC) systems consume a large amount of building energy consumption. HVAC systems have multiple varieties and configurations. One type of commercial HVAC systems that has not received enough attention is air-water systems. These systems are commonly used in office buildings and hotels where a higher degree of temperature control is needed. Few works have considered the modeling and optimization of this type of system. This article aims at providing a convex model for an air-water HVAC system. Moreover, a way to compensate for modeling and approximation errors and handling the uncertainties is provided. This is achieved through the use of the adjustable robust optimization theory. The aim of the optimization is to minimize the energy consumption while ensuring the temperature comfort. Both deterministic and robust formulations are provided, tested, and compared. The results showed that the temperature comfort can be ensured while considering modeling approximations and uncertainties.
      PubDate: THU, 14 SEP 2023 10:01:50 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Frequency Security Constrained Robust Unit Commitment for Sufficient
           Deployment of Diversified Frequency Support Resources

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      Authors: Kun Li;Xiaomeng Ai;Jiakun Fang;Shichang Cui;Yuang Feng;Dong Liu;Pan Gu;Weidong Qiu;Jinyu Wen;
      Pages: 1725 - 1737
      Abstract: This article proposes a frequency security constrained unit commitment (FSC-UC) model for sufficient deployment of diversified frequency support resources. Specifically, the diversities in generators’ inertial response capability, primary frequency response (PFR) ramping capability, and quasi-steady-state (QSS) PFR power capability are integrated into FSCs to ensure post-contingency frequency security. Moreover, we analyze the opposite impacts of upper/lower variable renewable energy (VRE) deviation, brought by the VRE uncertainties, on frequency security. Hence, an asymmetric robust re-dispatch strategy (ARRS) is proposed to handle the power balance and ensure frequency security robustness in all stochastic VRE scenarios. Case studies on a modified IEEE 6-bus system and a real provincial power system in Northwest China validate the effectiveness and scalability of the proposed FSCs and ARRS.
      PubDate: FRI, 15 SEP 2023 10:02:27 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Grid-Current Control With Inverter-Current Feedback Active Damping for LCL
           Grid-Connected Inverter

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      Authors: Nitin Upadhyay;Narayana Prasad Padhy;Pramod Agarwal;
      Pages: 1738 - 1749
      Abstract: The inverter-current proportional feedback (ICPF) active damping (AD) for an LCL grid-connected inverter (LCL-GCI) suffers from adverse gain reduction and loss of inductive ability in the low-frequency zone, making it unsuitable for active damping. To overcome the limitations of ICPF-AD, inverter-current bandpass filter feedback (ICBFF) AD is more conducive to suppressing the resonance of LCL-GCI. However, it is found that the system time delay constrains the damping capability of ICBFF-AD to resonance frequencies lower than those achievable with ICPF-AD. Therefore, this article proposes a second-order lead filter (SOLF) in cascade with the bandpass filter (BF) as an AD controller for inverter-current feedback AD. The analysis illustrates that cascading a SOLF with BF in the AD loop preserves the LCL filter's low-frequency gain and inductive nature resulting in improved dynamic response as compared to the ICPF-AD. Additionally, the cascaded filter AD allows the damping of higher resonance frequency with better noise immunity. The design approach for BF and SOLF is proposed and the effectiveness of the cascaded AD controller in the presence of different grid impedance is presented. The experimental results from a 10 kW laboratory setup corroborate the theoretical analysis.
      PubDate: TUE, 19 SEP 2023 10:03:12 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Observer-Based High-Order Sliding Mode Control of DFIG-Based Wind Energy
           Conversion Systems Subjected to Sensor Faults

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      Authors: Yashar Mousavi;Geraint Bevan;Ibrahim Beklan Kucukdemiral;Afef Fekih;
      Pages: 1750 - 1759
      Abstract: Recent advances in technology have paved the way for the increased penetration of wind energy conversion systems (WECSs) into the grid, worldwide. However, the existence of model uncertainties and intermittency of wind power can lead to malfunction of the stabilizing controllers and degrade the WECSs' power production performance. In this work, a compound control scheme comprising active fault-tolerant fractional-order nonsingular terminal sliding mode controllers (AFTSMCs) and a sliding mode observer (SMO) is developed to enhance the robustness of doubly-fed induction generator (DFIG)-based WECSs against uncertainties and maintain their desired performance. The developed AFTSMCs alleviate the chattering problem and overcome the compromise between fast response and the undesirable chattering problem. At the same time, it performs the speed trajectory tracking and rotor current regulation tasks. Moreover, under inevitable false fault detections due to unavoidable gradual performance degradations in the current sensors, a tolerance boundary is circumscribed for actual faults occurrence, allowing the developed robust SMO to estimate and reconstruct the rotor current during sensor faults with a high level of reliability. Evaluations of comparative performance are provided and validate the cooperative fault-tolerant method's superior control performance over other advanced approaches.
      PubDate: FRI, 22 SEP 2023 09:18:16 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • A Comparative Study of Thermally and Electromagnetically Driven Flow in
           the Electrolyte of Liquid Metal Batteries and Their Effects on Ion
           Transport

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      Authors: Xianbo Zhou;Chenglian Gao;Kangli Wang;Kai Jiang;Haomiao Li;
      Pages: 1760 - 1769
      Abstract: High-temperature liquid metal batteries (LMBs) are regarded as a promising candidate for grid-scale stationary energy storage. Numerical simulation is an important method to investigate physical phenomena such as fluid flow and mass transfer inside the LMB. At present, most models of the LMB electrolyte treat molten salt as a conductive fluid with a certain conductivity, while ignoring the ion distribution inside it. In this work, we develop a multi-field coupled model of LMB and comparatively analyze the thermally driven flow and electromagnetically driven flow in the molten salt electrolyte for the first time. Subsequently, we discuss the effects of flow on ion transport and electrochemical performance. Additionally, this model elucidates some experimental phenomena, such as the origin of the inhomogeneous deposition of intermetallic compounds and the reason why LMB can withstand ultra-high current densities. This work provides a deeper understanding of the internal mechanism of liquid metal batteries.
      PubDate: TUE, 26 SEP 2023 09:16:51 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Energy Theory Based Dynamic Adaptive Phasor Estimation for Smart Electric
           Grid

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      Authors: HyoJong Lee;Chuan Qin;Anurag K. Srivastava;
      Pages: 1770 - 1779
      Abstract: Phasor measurement units (PMUs) have been widely deployed for power grid monitoring, supporting system analytics, protection, automation, and control. However, with the continuous infiltration of inverter resources, the smart grid introduces more inherent uncertainties, leading to system state transformation. The most common method used by PMUs to estimate phasors is discrete Fourier transform (DFT) for 50 Hz and 60 Hz fundamental frequency, which is not applicable to capture dynamic disturbances under non-nominal frequency conditions. Unlikely, the modern grid operates more dynamically than the traditional power grid. The attenuated phasors can be produced if the grids operate at undesired frequencies during oscillation or dynamic events. The mono-phasor estimation algorithm may not fit all grid possible operating conditions. This article proposes the wavelet transform (WT) based phasor estimation algorithm for both PMU classes. The phasor estimation algorithm is dynamically switched among the best options using energy theory for higher performance of the PMU-based applications. The proposed phasor estimation architecture simulation results indicate superior measurement accuracy performance.
      PubDate: THU, 28 SEP 2023 09:17:21 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Investigation on Transient Stability Enhancement of Multi-VSG System
           Incorporating Resistive SFCLs Based on Deep Reinforcement Learning

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      Authors: Lei Chen;Jingguang Tang;Xuefeng Qiao;Hongkun Chen;Jiahui Zhu;Yuqi Jiang;Zekai Zhao;Ruize Hu;Xinyi Deng;
      Pages: 1780 - 1793
      Abstract: Virtual synchronous generator (VSG) strategy is an effective means for renewable energy sources to be connected to power grids. Meanwhile, a greater focus should be on the multi-VSG system's (MVS) transient stability issue. Regarding the MVS with resistive superconducting fault current limiters (R-SFCLs), this article proposes a control method based on deep reinforcement learning (DRL) agent for increasing the transient stability. Firstly, the theoretical model of the MVS incorporating R-SFCLs is established, and R-SFCLs are used to limit the fault current in VSGs and keep the fault ride-through (FRT) operation. Then, the working mechanism of the proposed method is elaborated, by designing the Markov decision process (MDP) model of transient control, and applying the improved softmax deep deterministic policy gradients (SD2) algorithm to train the DRL agent. The advanced time series feature extraction network (TSFEN) based on the convolutional neural network (CNN) and gate recurrent unit (GRU) is suggested to enhance the actor network and critic network of the SD2. A detailed simulation model is created using MATLAB, and a comparison with the traditional VSG control, only R-SFCL, deep deterministic policy gradients (DDPG) algorithm, and improved power loop scheme is conducted. From multiple cases, the proposed approach can satisfactorily boost the transient stability of the MVS, and the generalization ability of the DRL agent under different untrained scenarios is validated. The proposed method's validity and suitability are well-confirmed.
      PubDate: MON, 02 OCT 2023 09:18:57 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Spatio-Temporal Graph Neural Network and Pattern Prediction Based
           Ultra-Short-Term Power Forecasting of Wind Farm Cluster

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      Authors: Xiaoyan Liu;Yiran Zhang;Zhao Zhen;Fei Xu;Fei Wang;Zengqiang Mi;
      Pages: 1794 - 1803
      Abstract: Accurate and timely ultra-short-term wind farm cluster power forecasting is significant for real-time dispatch and frequency regulation of power grids. Distinguishing different types of power fluctuation patterns based on fluctuation process analysis and training prediction models separately based on pattern partitioning results, is beneficial for improving the prediction accuracy of wind farm cluster power. However, existing pattern partitioning methods have a single perspective and have not yet formed a multi-dimensional evaluation routine to quantify the fluctuation characteristics of different patterns. Furthermore, for wind farm clusters, there is a lack of consideration of the dynamic spatio-temporal relationship between adjacent wind farm stations under different power fluctuation patterns. To make up for these deficiencies, this article proposes an ultra-short-term wind farm cluster power forecasting model based on power fluctuation pattern recognition and spatio-temporal graph neural network pattern prediction. First, the extreme points are statistically analyzed, and the wind farm cluster power is divided into different fluctuation processes. Then four indicators are summarized from the time stationarity and amplitude volatility of these fluctuation processes to guide the partition of power fluctuation patterns. Finally, considering the dynamic spatio-temporal correlation between adjacent stations under various fluctuation patterns, the spatio-temporal graph neural network is exploited for model training for each fluctuation pattern. After identifying the fluctuation patterns of the wind power series in the test set, the corresponding trained model is used to obtain the final prediction results. Experiments with other benchmarks show that the proposed method is superior on real wind farm cluster power dataset.
      PubDate: MON, 02 OCT 2023 09:18:57 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Adaptive Feature Selection and GCN With Optimal Graph Structure-Based
           Ultra-Short-Term Wind Farm Cluster Power Forecasting Method

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      Authors: Honglai Xu;Yiran Zhang;Zhao Zhen;Fei Xu;Fei Wang;
      Pages: 1804 - 1813
      Abstract: Cluster-level wind power forecasting is of great significance for the centralized integration of wind power into the grid. Studies have shown that adjacent wind farms exhibit high spatial-temporal correlation. As an extension of the convolutional neural networks (CNN), the graph convolutional neural networks (GCN) can effectively extract spatial-temporal features from the power and numerical weather prediction (NWP) data of adjacent wind farms. However, the strong correlation among NWP data from various wind farms within the same region inevitably leads to higher redundancy. Directly modeling all the wind farms of the cluster as a graph input for GCN would result in increased complexity and computational costs of the prediction model, thereby affecting the performance and accuracy of the prediction model. Therefore, it is necessary to perform feature selection on the wind farm cluster. To address the issue of manually determining the optimal number of features in the traditional maximum relevance minimum redundancy (MRMR) algorithm through cross-validation, an adaptive MRMR algorithm is proposed by introducing conditional mutual information. This algorithm automatically determines the optimal number of features in the feature subset. The optimal feature subsets obtained are used to construct an optimal graph structure as input for GCN in wind farm cluster power forecasting. Simulation results demonstrate that the proposed method has lower data and computational costs while exhibiting outstanding performance in improving power prediction accuracy.
      PubDate: TUE, 03 OCT 2023 09:18:25 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Photovoltaic Panel Fault Detection and Diagnosis Based on a Targeted
           Transformer-Style Model

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      Authors: Shengxi Li;Hui Chen;Ao Zhang;Chunyang Gong;Muhammad Ilyas Menhas;Weibin Liang;Zhixin Wang;Ning Yang;
      Pages: 1814 - 1826
      Abstract: The number of photovoltaic power plants is increasing rapidly and consequently their stability, efficiency and safety have become more important. In view, it is necessary to regularly detect, diagnose and maintain photovoltaic modules in a timely manner. In this work, a new image classification network based on the MPViT network structure is designed to solve the problem of fault detection and diagnosis of photovoltaic panels using image processing methods. Owing to the similarity between different types of photovoltaic panels an Enhanced Local Self-Attention block (ELSA block) is introduced to improve the learning ability of the model's local features so as to improve the model's ability to differentiate categories. Binary classification and multi-classification experiments are carried out on two datasets namely the photovoltaic module dataset based on infrared imaging (dataset1), and the photovoltaic module dataset based on electroluminescence imaging (dataset2). The M-E model (MPViT model introduced with ELSA block) achieves 94.1$\%$ and 88.5$\%$, 90.7$\%$ and 86.4$\%$ accuracy for binary classification and multi-class classification on dataset1 and dataset2 better than MPViT respectively.
      PubDate: MON, 09 OCT 2023 09:18:58 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • An Efficient Method to Localize and Quantify Axial Displacement in
           Transformer Winding Using Support Vector Machines

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      Authors: A. Muhammed;P. Saji;Mojiza J;Vinod V;Sunil Kumar P. R;
      Pages: 1827 - 1836
      Abstract: In power systems, power transformers are critical components that play a key role in delivering electricity to consumers. However, transformers are also vulnerable to various faults, such as winding faults, insulation failures, and internal short circuits, which can cause significant disruptions and lead to costly downtime. It is needless to emphasize that the early detection of mechanical faults in the transformer winding is inevitable for its continuous operation. Among the different condition monitoring and diagnostic techniques, Frequency Response Analysis(FRA) has the potential to detect even incipient mechanical displacements/deformations. In the present analysis, support vector Machine (SVM), a supervised machine learning technique is used to locate and quantify the axial displacement with the help of features extracted from the FRA traces of the transformers. In the training phase, a series of axial displacements is simulated in finite element software, and corresponding equivalent circuit parameters are used to generate FRA traces. Furthermore, features are extracted from these FRA traces to train the SVM model to enable it to predict the location and quantity of axial displacement accurately. Finally, the accuracy of this SVM model is tested through randomly created axial displacement data on a practical 3.3 MVA transformer winding. The result indicates the ability of this technique to be used as an intelligent and accurate diagnostic to locate and quantify axial displacements in the transformer winding.
      PubDate: MON, 16 OCT 2023 09:18:15 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Predictive Current Control of Switched Reluctance Machine for Accurate
           Current Tracking to Enhance Torque Performance

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      Authors: Syed Shahjahan Ahmad;Mouli Thirumalasetty;G. Narayanan;
      Pages: 1837 - 1848
      Abstract: Accurate tracking of reference current wave shapes is essential to obtain the desired average torque, as well as minimize torque ripple and losses of switched reluctance motor (SRM). This article proposes a predictive control technique for accurate tracking of the current reference in an SRM drive based on a simplified piecewise linear flux-linkage model. The proposed technique eliminates extensive lookup tables and requires only a small set of model parameters, resulting in efficient memory utilization. The performance of the proposed method is evaluated for two different current shapes at various operating speeds and load torques. Simulations and experiments show that the proposed technique offers better or comparable performance over state-of-the-art lookup table-based gain-scheduling PI, sliding mode, and two existing predictive control methods. Further, the proposed technique offers the lowest torque ripple among all the above controllers. Since predictive control is based on machine models, any error in modeling can potentially lead to deterioration in tracking and instability. It has been theoretically proved that the proposed controller ensures stability even with modeling errors as high as 200% in incremental inductance. Additionally, simulation results are presented to show the effect of varying three crucial model parameters on the current tracking performance of the proposed controller. The model parameters are varied within a range of −30% to +50% of their nominal values at three different speeds. The experimental results confirm very good current tracking performance even in the presence of large modeling errors.
      PubDate: TUE, 17 OCT 2023 09:17:39 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Event-Driven Q-Routing-Based Dynamic Optimal Reconfiguration of the
           Connected Microgrids in the Power Distribution System

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      Authors: Aravind Ingalalli;Sukumar Kamalasadan;Zerui Dong;Guna R. Bharati;Sudipta Chakraborty;
      Pages: 1849 - 1859
      Abstract: The operation of connected microgrids enables the availability of local distributed energy resources (DER) at the network level. During grid events such as electric faults, part of the power distribution network needs to be isolated such that the healthy part of the network can operate generally through optimal reconfiguration. Most of the topology agnostic reconfiguration schemes are complicated, computationally expensive, and offer a single optimal path. To overcome these disadvantages, a reinforcement learning-based extended q-routing method is proposed in this article to achieve optimal network reconfiguration. The proposed method utilizes a model-free adaptive learning technique, thus efficiently discovering optimal paths in a dynamically changing network. To validate the proposed method in a real-time environment, a detailed dynamic distribution network model is developed, including primary and secondary control of integrated DERs and the protection functions. Furthermore, event-driven communication is designed to exchange data between the dynamic network model and the reconfiguration agent. The results obtained from the real-time agent-in-the-loop set-up showcase the effectiveness of the proposed method that achieves network reconfiguration within 1.5 s.
      PubDate: THU, 19 OCT 2023 09:17:10 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Optimal Control Path for DAB Based Solid-State Transformer

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      Authors: Karthik Singh Parihar;Wajahat Khan;Jahangeer Ahmad Dar;Mukesh Kumar Pathak;
      Pages: 1860 - 1869
      Abstract: This article proposes a control strategy for single-stage Dual active bridge (DAB) based Solid-State Transformer (SST) converter. The proposed control strategy utilizes two control variables to develop a control path that increases soft switching range while minimizing the transformer current stress. The article analyzes zero voltage switching (ZVS) conditions and transformer current characteristics for single-stage DAB based SST converter. Analytical expressions are derived for implementing the control strategy, therefore no lookup tables are used. The performance of the proposed control strategy is compared with the conventional phase-shift (PS) control technique in terms of ZVS range and peak transformer current. Finally, the effectiveness of the proposed control strategy and the validity of the theoretical analysis are confirmed by experimental data.
      PubDate: MON, 23 OCT 2023 09:21:57 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Low-Cost Condition Monitoring System for Smart Buildings and Industrial
           Applications

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      Authors: Andrea Toscani;Nicholas Rocchi;Daniel Pinardi;Marco Binelli;Leonardo Saccenti;Angelo Farina;Stefano Pavoni;Marcello Vanali;
      Pages: 1870 - 1878
      Abstract: Condition Monitoring (CM) aims at damage identification through the measurement of various data collected from the systems under investigation (civil structures, mechanical parts, or industrial machineries) such as acceleration, temperature, displacement, and dynamic properties variation. Synchronization between the measured signals is mandatory for the processing of diagnostic metrics and modal analysis, which is why most of the monitoring systems today consist of a centralized acquisition unit to which analog transducers are connected. However, this solution entails a high cost of equipment and the use of long analog cables for each transducer. A full-digital network solution has been developed to solve these problems. The acquisition network is composed of Interface Boards for interfacing with the data storage system (e.g., a personal computer) and Acquisition Nodes integrating Micro Electro-Mechanical Systems (MEMS) digital triaxial accelerometers. The Interface Boards can be connected via Universal Serial Bus (USB) or Local Area Network (LAN), while the Acquisition Nodes are connected in daisy-chain via a digital bus implemented on an Unshielded Twisted Pair (UTP) cable. The proposed solution simplifies wiring, reduces system cost, and provides accurately synchronized signals. Experimental measurements on a truss model and a motor test bench for ball bearing failures diagnostic are presented, to demonstrate the effectiveness of the solution in civil and industrial applications, compared to a traditional analog laboratory-grade system.
      PubDate: TUE, 24 OCT 2023 09:18:36 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Fault Diagnosis Method of Lithium-Ion Battery Leakage Based on
           Electrochemical Impedance Spectroscopy

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      Authors: Yanru Zhang;Pengfei Zhang;Jing Hu;Caiping Zhang;Linjing Zhang;Yubin Wang;Weige Zhang;
      Pages: 1879 - 1889
      Abstract: Electrolyte leakage may cause lithium-ion battery performance degradation, and even lead to short-circuit, resulting in serious safety accidents. In order to improve the safety of lithium-ion battery, it is necessary to detect electrolyte leakage in time. This paper presents a fault diagnosis method for electrolyte leakage of lithium-ion based on support vector machine (SVM) by electrochemical impedance spectroscopy (EIS) test. And the distribution of relaxation time (DRT) method is also employed to analyze the effect of leakage on the dynamic reaction process with full and half cells. In the proposed method, the EIS and DRT features are all used for the diagnosis to improve accuracy. Furthermore, the sensitivity of different features, the accuracy of battery classification under different cycles and state of charge were also analyzed to reduce diagnostic time by decreasing the test frequency range and SOC points and then validate the feasibility of the method.
      PubDate: TUE, 24 OCT 2023 09:18:36 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Optimal DG Planning Incorporating Energy Management for an Economical and
           Resilient Smart Distribution System

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      Authors: Ram Prakash;B. Lokeshgupta;S. Sivasubramani;Tarakanath Kobaku;Vivek Agarwal;
      Pages: 1890 - 1901
      Abstract: In this study, a novel application of multi-objective (MO) optimization methodology is presented for distributed generation (DG) planning incorporating energy management (EM). The MO problem considers the DG cost reduction, system reliability enhancement, and power loss minimization objectives to determine the optimal capacity and position of renewable and dispatchable DG. The initial capital, maintenance and operation, emission, and fuel costs make up the proposed long-term DG cost. Expected outage cost (ECOST) due to interrupted power supply is evaluated to estimate the reliability of the distribution network. The proposed MO optimization problem is optimized using a cooperative game theory technique. The technique is based on the super-criterion and bargaining model concept. In this game process, each objective acts as a participant, and ultimately, all stakeholders are able to achieve win-win outcomes through collective negotiations. Various scenarios and case studies are performed on the modified IEEE 33-bus system with an hourly profile of solar photovoltaic arrays, wind turbines, and load demand. Simulation results illustrate the efficacy of the proposed approach. Moreover the real-time applicability of the proposed model is validated through an experimental setup on the OPAL-RT platform.
      PubDate: WED, 01 NOV 2023 09:18:16 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Parametric and Catastrophic Failures of Metallized Film Capacitors Under
           High Voltage Stress

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      Authors: Ivan O. Ivanov;Dmitry Y. Glivenko;Ahmet A. Hojamov;Alexey V. Pechnikov;
      Pages: 1902 - 1908
      Abstract: Operation ability of different metallized film capacitors under high voltage stress was investigated. The automated ramp voltage test method was suggested. The experimental setup and software for experimental data processing were developed. Self-healing characteristics in the wide temperature range were obtained. It was found that increasing of operating temperature leads to decreasing of self-healing events number which corresponds to parametric or catastrophic failure. The critical values of cumulative self-healing energy for investigated capacitors until parametric and catastrophic failures were determined. Statistical analysis of self-healing events showed the presence of two types of processes with different energy distributions.
      PubDate: FRI, 27 OCT 2023 09:17:22 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Uncertainty Aware Learning Model for Thermal Comfort in Smart Residential
           Buildings

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      Authors: Srinivas Yelisetti;Vikash Kumar Saini;Rajesh Kumar;Ravita Lamba;Akash Saxena;
      Pages: 1909 - 1918
      Abstract: Smart energy management for homes is a potential area of research. Establishing a trade-off between occupant comfort and energy saving is quite a crucial issue to handle. To address this issue, the paper presents a multi-objective optimisation routine-based approach for handling this conflicting trade-off. Air quality, visual, and thermal comforts are important factors when considering occupant comfort. Heating, ventilation, and air conditioning systems employ the predicted values for comfort temperature and air quality comfort inside the room. The lighting system is used to maintain visual comfort inside the room. A data-driven strategy is put out in this research to forecast user thermal comfort for each occupant in residential homes. Six deep-learning approaches are applied to estimate each occupant's interior comfort temperature. These approaches are evaluated with the help of mean square error (MSE), mean absolute percentage error (MAPE), root mean square error (RMSE), normalised mean square error (NMSE), and R-squared score (R2 score). Bi-directional gated recurrent units (Bi-GRU) have shown to be the best. Bi-GRU outperforms in the following metrics: MSE, MAPE, RMSE, NMSE, and normalised R2 score values are 0.0104, 8.1768, 0.1022, 7.5121, and 1, respectively; these metrics are found optimal when compared with other techniques. The overall system is optimised with the application of particle swarm optimisation. Summer, winter, and monsoon seasons weather data in India are used to test the proposed model. The influence of temperature uncertainty on total energy consumption, overall comfort, and energy consumption cost is also being examined in all three seasons.
      PubDate: MON, 30 OCT 2023 09:19:29 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • An Adaptive Neuro-Fuzzy Model-Based Algorithm for Fault Detection in PV
           Systems

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      Authors: Mary Pa;Mohammad Nasir Uddin;Nima Rezaei;
      Pages: 1919 - 1927
      Abstract: This article presents an intelligent algorithm-based fault detection scheme to improve the reliability and sustainability of a photovoltaic (PV) system. The PV systems are extremely susceptible to power grid transients and their operation may suffer drastically during faults located within the solar arrays, power electronics, and the inverter. Thus, it is significantly important to develop an intelligent mechanism to detect any type of fault or abnormalities at the shortest possible time and provide security for the solar system. In order to accomplish that, an adaptive neuro-fuzzy inference system (ANFIS) is developed to distinguish between normal, and faulty operation of a grid-connected PV system. A large dataset from real-time laboratory experiment using TBD125x125-36-P PV module, which includes the current, and voltage characteristic of PV is extracted, preprocessed and used in the training of the machine learning algorithm. The performance of the proposed intelligent fault detection scheme is also compared with other popular machine learning algorithms, where ANFIS have demonstrated outstanding results, with accuracy rate of 95.4%. Furthermore, the proposed technique is significantly more robust, straightforward, and requires less implementation time compared to other machine learning techniques such as, K nearest neighbor, decision tree, Naïve Bayes, Ensemble, linear discriminant analysis, support vector machine, and finally neural network. Thus, the developed ANFIS based intelligent technique will enhance the reliability of the PV system through minimizing the maintenance cost, saving time and energy.
      PubDate: TUE, 31 OCT 2023 09:17:01 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Development of a Portable SF6/N2 Mixed Gas Charging Device for On-Site
           Modification of Gas Insulated Current Transformer

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      Authors: Dingge Yang;Tongyu Liu;Yuyang Zhao;Yu Shang;Lu Pu;Bo Niu;Yanhua Han;Weidong Qi;Jingfeng Wu;Zihao Yang;Linyuan Ren;Zichen Deng;Weidong Ding;Yanan Wang;
      Pages: 1928 - 1937
      Abstract: In this article, a portable gas charging device for SF6/N2 gas-insulated current transformer is developed to meet the demands of on-site modification of SF6/N2 gas-filled current transformer. This device has the functions of SF6 retrieving, vacuum pumping, mixed gas filling, and mixed gas ratio detection. This device adopts the partial pressure controlling method to realize the gas mixture ratio. By filling the mixed gas successively, the required pressure value is finally achieved without presetting the total volume of inflating gas. The operation process is simple and intuitive, and the operation efficiency is high. The built-in temperature detection and pressure detection module can carry out real-time detection and temperature correction for the charging pressure of mixed gas, improving the accuracy of the charging device. A buffer cavity is designed to speed up the homogenization of the mixed gas in the equipment cavity. The gas in the equipment cavity is poured into the buffer cavity repeatedly to force it to mix quickly, which reduces the time required for the gas to be set even and improves the charging efficiency. The experiment results show that the mixing ratio accuracy of the charging device can be controlled within 1%, and the pressure deviation can be controlled within 0.02 MPa. With the gas charging device, two current transformer on-site modifications have been successfully conducted.
      PubDate: WED, 01 NOV 2023 09:18:17 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Critical Flicker Frequency and Auditory Stimuli – Procedure Settings

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      Authors: Leoš Kukačka;Michaela Chmelařová;Jan Hergesel;Pascal Dupuis;Georges Zissis;
      Pages: 1938 - 1945
      Abstract: The standing standardized measure for the assessment of flicker severity, the light flickermeter (IEC TR 61547-1:2020), evaluates the flicker irritability level in reference conditions as a necessary simplification. This misestimates the actual level in the presence of other factors known to influence flicker visibility. One such factor is noise, which interacts with the visual system under specific circumstances. However, direct effect of noise or any auditory stimuli on the flicker visibility threshold is not yet understood. This article is concerned with the design of experiments aimed at determining whether the critical flicker frequency (CFF) is subject to change when the observer is exposed to pulsating sounds. The article describes the work done in designing the experiments and also reveals data from a preliminary campaign. Data collected so far are insufficient to establish a direct link between pulsating sound and CFF, but are used to adjust the conditions of a wider campaign. Mathematical tools are developed to evaluate the experiment results using a probabilistic framework.
      PubDate: TUE, 19 SEP 2023 10:03:12 -04
      Issue No: Vol. 60, No. 1 (2023)
       
  • Modeling the Dynamic Behavior of DC Arcs

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      Authors: Lloyd B. Gordon;
      Pages: 1946 - 1955
      Abstract: AC arc flash hazards were recognized in 1982 and introduced into OSHA and NFPA 70E soon thereafter. DC arc flash hazards were being considered by 2007 and introduced into the 2012 NFPA 70E. Two methods were introduced in NFPA 70E to estimate dc incident energy, with little data available. In general, these methods overestimate the hazard when compared to recent laboratory data. This article will provide a high-level overview of (a) the current understanding of high-current, dc arc physics, (b) models presently used in performing dc incident energy analyses, and (c) recent laboratory studies to measure DC arc flash parameters for several voltages. This latest information will then be used to evaluate the accuracy of some existing dc arc hazard assessments, and to propose improved approaches to modeling the dynamic behavior of short, high-current, free-air arcs. These dynamic models proposed help to better predict the extinction behavior of such arcs. This work is applicable to slow risetime arcs, such as produced by dc power supplies, battery banks, super capacitors, and solar voltaic systems. It is not applicable to capacitor discharges as the fast risetime produces a supersonic shock wave and the arc behavior is beyond the scope of this article. Data analyzed is from the battery bank and electric transportation applications.
      PubDate: TUE, 05 SEP 2023 10:03:19 -04
      Issue No: Vol. 60, No. 1 (2023)
       
 
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  Subjects -> ELECTRONICS (Total: 207 journals)
Showing 1 - 200 of 277 Journals sorted by number of followers
IEEE Transactions on Aerospace and Electronic Systems     Hybrid Journal   (Followers: 336)
Control Systems     Hybrid Journal   (Followers: 289)
IEEE Transactions on Geoscience and Remote Sensing     Hybrid Journal   (Followers: 236)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 213)
Electronics     Open Access   (Followers: 177)
Advances in Electronics     Open Access   (Followers: 172)
Electronics For You     Partially Free   (Followers: 159)
Electronic Design     Partially Free   (Followers: 157)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 144)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 94)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 92)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 88)
IEEE Transactions on Industrial Electronics     Hybrid Journal   (Followers: 88)
IEEE Transactions on Software Engineering     Hybrid Journal   (Followers: 87)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 81)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 70)
IET Power Electronics     Open Access   (Followers: 69)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 66)
IEEE Embedded Systems Letters     Hybrid Journal   (Followers: 59)
IEEE Transactions on Industry Applications     Hybrid Journal   (Followers: 58)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 57)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 55)
Advances in Power Electronics     Open Access   (Followers: 50)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 46)
IEEE Nanotechnology Magazine     Hybrid Journal   (Followers: 44)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 42)
IEEE Transactions on Biomedical Engineering     Hybrid Journal   (Followers: 36)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 34)
IET Microwaves, Antennas & Propagation     Open Access   (Followers: 33)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 32)
Electronics Letters     Open Access   (Followers: 32)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 32)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 30)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 28)
Microelectronics and Solid State Electronics     Open Access   (Followers: 27)
International Journal of Aerospace Innovations     Full-text available via subscription   (Followers: 25)
Journal of Sensors     Open Access   (Followers: 23)
International Journal of Power Electronics     Hybrid Journal   (Followers: 23)
IEEE Reviews in Biomedical Engineering     Hybrid Journal   (Followers: 21)
IEEE/OSA Journal of Optical Communications and Networking     Hybrid Journal   (Followers: 20)
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 19)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 18)
IET Wireless Sensor Systems     Open Access   (Followers: 18)
IEEE Transactions on Signal and Information Processing over Networks     Hybrid Journal   (Followers: 17)
Journal of Artificial Intelligence     Open Access   (Followers: 16)
Circuits and Systems     Open Access   (Followers: 16)
Archives of Electrical Engineering     Open Access   (Followers: 16)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 16)
International Journal of Control     Hybrid Journal   (Followers: 14)
Advances in Microelectronic Engineering     Open Access   (Followers: 14)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 14)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 13)
IETE Journal of Research     Open Access   (Followers: 13)
IEEE Solid-State Circuits Magazine     Hybrid Journal   (Followers: 13)
International Journal of Advanced Electronics and Communication Systems     Open Access   (Followers: 13)
Nature Electronics     Hybrid Journal   (Followers: 13)
Machine Learning with Applications     Full-text available via subscription   (Followers: 13)
Solid-State Electronics     Hybrid Journal   (Followers: 12)
IEEE Transactions on Broadcasting     Hybrid Journal   (Followers: 12)
IEEE Transactions on Learning Technologies     Full-text available via subscription   (Followers: 12)
IEEE Women in Engineering Magazine     Hybrid Journal   (Followers: 12)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 12)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 12)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 11)
Frontiers in Electronics     Open Access   (Followers: 11)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 10)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 10)
Batteries     Open Access   (Followers: 10)
Superconductivity     Full-text available via subscription   (Followers: 10)
IETE Technical Review     Open Access   (Followers: 9)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 9)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 9)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 9)
ACS Applied Electronic Materials     Open Access   (Followers: 9)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 8)
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 8)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 8)
Journal of Signal and Information Processing     Open Access   (Followers: 8)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 8)
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 8)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 8)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 8)
International Journal of Antennas and Propagation     Open Access   (Followers: 7)
Annals of Telecommunications     Hybrid Journal   (Followers: 7)
IEEE Transactions on Autonomous Mental Development     Hybrid Journal   (Followers: 7)
IEEE Magnetics Letters     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 7)
Open Journal of Antennas and Propagation     Open Access   (Followers: 7)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 7)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 7)
Energy Storage Materials     Full-text available via subscription   (Followers: 7)
Chinese Journal of Electronics     Open Access   (Followers: 7)
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access   (Followers: 7)
Electronic Markets     Hybrid Journal   (Followers: 6)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 6)
International Journal of Electronics     Hybrid Journal   (Followers: 6)
Journal of Electronics (China)     Hybrid Journal   (Followers: 6)
Journal of Field Robotics     Hybrid Journal   (Followers: 6)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 6)
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 6)
Australian Journal of Electrical and Electronics Engineering     Hybrid Journal   (Followers: 6)
EPE Journal : European Power Electronics and Drives     Hybrid Journal   (Followers: 6)
Advanced Materials Technologies     Hybrid Journal   (Followers: 6)
Nanotechnology, Science and Applications     Open Access   (Followers: 5)
IEEE Transactions on Services Computing     Hybrid Journal   (Followers: 5)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 5)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 5)
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 5)
Metrology and Measurement Systems     Open Access   (Followers: 5)
IEEE Pulse     Hybrid Journal   (Followers: 5)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 5)
Journal of Optoelectronics Engineering     Open Access   (Followers: 5)
Batteries & Supercaps     Hybrid Journal   (Followers: 5)
Journal of Power Electronics     Hybrid Journal   (Followers: 5)
Sensors International     Open Access   (Followers: 5)
e-Prime : Advances in Electrical Engineering, Electronics and Energy     Open Access   (Followers: 5)
Materials Today Electronics     Open Access   (Followers: 5)
Networks: an International Journal     Hybrid Journal   (Followers: 4)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 4)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 4)
IEEE Transactions on Haptics     Hybrid Journal   (Followers: 4)
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 4)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 4)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
IETE Journal of Education     Open Access   (Followers: 4)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 4)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 4)
EPJ Quantum Technology     Open Access   (Followers: 4)
Wireless and Mobile Technologies     Open Access   (Followers: 4)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 4)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
Informatik-Spektrum     Hybrid Journal   (Followers: 3)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 3)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 3)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal   (Followers: 3)
Power Electronic Devices and Components     Open Access   (Followers: 3)
Journal of Nuclear Cardiology     Hybrid Journal   (Followers: 2)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Journal of Semiconductors     Full-text available via subscription   (Followers: 2)
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 2)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 2)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 2)
Journal of Information and Telecommunication     Open Access   (Followers: 2)
Advancing Microelectronics     Hybrid Journal   (Followers: 2)
IET Smart Grid     Open Access   (Followers: 2)
IET Energy Systems Integration     Open Access   (Followers: 2)
Transactions on Electrical and Electronic Materials     Hybrid Journal   (Followers: 2)
Energy Storage     Hybrid Journal   (Followers: 2)
IEEE Open Journal of the Industrial Electronics Society     Open Access   (Followers: 2)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 1)
Journal of Electrical Bioimpedance     Open Access   (Followers: 1)
International Journal of High Speed Electronics and Systems     Hybrid Journal   (Followers: 1)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Електротехніка і Електромеханіка     Open Access   (Followers: 1)
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 1)
Edu Elektrika Journal     Open Access   (Followers: 1)
Technical Report Electronics and Computer Engineering     Open Access   (Followers: 1)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 1)
Open Electrical & Electronic Engineering Journal     Open Access   (Followers: 1)
International Journal of Hybrid Intelligence     Hybrid Journal   (Followers: 1)
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access   (Followers: 1)
Solid State Electronics Letters     Open Access   (Followers: 1)
Ural Radio Engineering Journal     Open Access   (Followers: 1)
IEEE Open Journal of Circuits and Systems     Open Access   (Followers: 1)
IEEE Letters on Electromagnetic Compatibility Practice and Applications     Hybrid Journal   (Followers: 1)
Elektronika ir Elektortechnika     Open Access   (Followers: 1)
Automatika : Journal for Control, Measurement, Electronics, Computing and Communications     Open Access   (Followers: 1)
npj Flexible Electronics     Open Access  
Transactions on Cryptographic Hardware and Embedded Systems     Open Access  
Emitor : Jurnal Teknik Elektro     Open Access  
IEEE Solid-State Circuits Letters     Hybrid Journal  
IEEE Open Journal of Industry Applications     Open Access  
IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology     Hybrid Journal  
Journal of Electronic Science and Technology     Open Access  
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Journal of Engineered Fibers and Fabrics     Open Access  
Jurnal Teknologi Elektro     Open Access  
IET Nanodielectrics     Open Access  
Elkha : Jurnal Teknik Elektro     Open Access  
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Jurnal Teknik Elektro     Open Access  
IACR Transactions on Symmetric Cryptology     Open Access  
Acta Electronica Malaysia     Open Access  
Bioelectronics in Medicine     Hybrid Journal  
Problemy Peredachi Informatsii     Full-text available via subscription  
Jurnal Rekayasa Elektrika     Open Access  
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Visión Electrónica : algo más que un estado sólido     Open Access  
Telematique     Open Access  
International Journal of Nanoscience     Hybrid Journal  
Semiconductors and Semimetals     Full-text available via subscription  

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