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ELECTRICAL ENGINEERING (105 journals)                     

Showing 1 - 105 of 105 Journals sorted alphabetically
3C TIC     Open Access   (Followers: 1)
Actuators     Open Access   (Followers: 4)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 4)
Advances in Microelectronic Engineering     Open Access   (Followers: 12)
Advances in Signal Processing     Open Access   (Followers: 12)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 24)
American Journal of Sensor Technology     Open Access   (Followers: 4)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 8)
Archives of Control Sciences     Open Access   (Followers: 3)
Archives of Electrical Engineering     Open Access   (Followers: 12)
Atom Indonesia     Open Access   (Followers: 1)
Case Studies in Mechanical Systems and Signal Processing     Open Access  
Circuits, Systems, and Signal Processing     Hybrid Journal   (Followers: 12)
Computers & Electrical Engineering     Hybrid Journal   (Followers: 9)
Edu Elektrika Journal     Open Access  
Electric Power Components and Systems     Hybrid Journal   (Followers: 7)
Electric Power Systems Research     Partially Free   (Followers: 18)
Electrical and Electronic Engineering     Open Access   (Followers: 31)
Electrical and Power Engineering Frontier     Open Access   (Followers: 24)
Electrical Engineering     Hybrid Journal   (Followers: 20)
Electrical Engineering and Automation     Open Access   (Followers: 8)
Electrical Engineering and Power Engineering     Open Access  
Electrical Engineering in Japan     Hybrid Journal   (Followers: 8)
Electrical, Control and Communication Engineering     Open Access   (Followers: 13)
Emerging and Selected Topics in Circuits and Systems     Hybrid Journal   (Followers: 9)
EURASIP Journal on Advances in Signal Processing     Open Access   (Followers: 7)
Ferroelectrics     Hybrid Journal   (Followers: 1)
Ferroelectrics Letters Section     Hybrid Journal   (Followers: 1)
Frequenz     Hybrid Journal   (Followers: 1)
Frontiers of Electrical and Electronic Engineering     Hybrid Journal   (Followers: 8)
IEA Electricity Information     Full-text available via subscription   (Followers: 4)
IEEE Access     Open Access   (Followers: 80)
IEEE Electrical Insulation Magazine     Full-text available via subscription   (Followers: 41)
IEEE Signal Processing Magazine     Full-text available via subscription   (Followers: 75)
IEEE Transactions on Control of Network Systems     Hybrid Journal   (Followers: 13)
IEEE Transactions on Dielectrics and Electrical Insulation     Hybrid Journal   (Followers: 14)
IEEE Transactions on Signal and Information Processing over Networks     Full-text available via subscription   (Followers: 10)
IEEJ Transactions on Electrical and Electronic Engineering     Hybrid Journal   (Followers: 15)
IET Control Theory & Applications     Hybrid Journal   (Followers: 23)
IET Electric Power Applications     Hybrid Journal   (Followers: 23)
IET Electrical Systems in Transportation     Hybrid Journal   (Followers: 9)
IETE Journal of Education     Open Access   (Followers: 4)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 2)
Indonesian Journal of Electrical Engineering and Computer Science     Open Access   (Followers: 14)
Ingeniería Electrónica, Automática y Comunicaciones     Open Access  
Integrated Ferroelectrics: An International Journal     Hybrid Journal   (Followers: 1)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 8)
International Journal of Electrical Engineering Education     Hybrid Journal   (Followers: 6)
International Journal of Electrical Power & Energy Systems     Open Access   (Followers: 22)
International Journal of Emerging Electric Power Systems     Hybrid Journal   (Followers: 7)
International Journal of Monitoring and Surveillance Technologies Research     Full-text available via subscription   (Followers: 4)
International Journal of Nano Devices, Sensors and Systems     Open Access   (Followers: 10)
International Journal of Nuclear Security     Open Access   (Followers: 1)
International Journal of Turbomachinery, Propulsion and Power     Open Access   (Followers: 4)
International Journal on Communication     Full-text available via subscription   (Followers: 14)
International Journal on Control System and Instrumentation     Full-text available via subscription   (Followers: 15)
International Journal on Electrical and Power Engineering     Full-text available via subscription   (Followers: 9)
International Journal on Signal and Image Processing     Full-text available via subscription   (Followers: 6)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
International Transactions on Electrical Energy Systems     Hybrid Journal   (Followers: 8)
Izvestiya Vysshikh Uchebnykh Zavedenii. Materialy Elektronnoi Tekhniki : Materials of Electronics Engineering     Full-text available via subscription  
J3eA     Open Access   (Followers: 2)
Journal of Control, Automation and Electrical Systems     Hybrid Journal   (Followers: 9)
Journal of Electrical and Computer Engineering     Open Access   (Followers: 9)
Journal of Electrical and Computer Engineering Innovations     Open Access   (Followers: 4)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 20)
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering     Open Access   (Followers: 25)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 7)
Journal of Electrical Systems and Information Technology     Open Access   (Followers: 7)
Journal of Field Robotics     Hybrid Journal   (Followers: 2)
Journal of International Council on Electrical Engineering     Open Access  
Journal of Micro-Bio Robotics     Hybrid Journal  
Journal of Microwaves, Optoelectronics and Electromagnetic Applications     Open Access   (Followers: 9)
Journal of Power Technologies     Open Access   (Followers: 6)
Journal of the Society for Information Display     Hybrid Journal  
Journal of World's Electrical Engineering and Technology     Open Access   (Followers: 2)
Journal of Zhejiang University SCIENCE C     Hybrid Journal  
Jurnal Ilmiah Mahasiswa SPEKTRUM     Open Access  
Jurnal Nasional Teknik Elektro     Open Access   (Followers: 4)
Jurnal Rekayasa Elektrika     Open Access  
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 2)
Majlesi Journal of Electrical Engineering     Open Access   (Followers: 1)
Micro and Nano Systems Letters     Open Access   (Followers: 5)
Nanotechnology Development     Open Access   (Followers: 20)
npj Materials Degradation     Open Access  
Oil, Gas, Coal and Electricity - Quarterly Statistics - Electricite, charbon, gaz et petrole - Statistiques trimestrielles     Full-text available via subscription   (Followers: 9)
Photovoltaics, IEEE Journal of     Hybrid Journal   (Followers: 16)
Quantum Beam Science     Open Access   (Followers: 1)
Recent Advances in Communications and Networking Technology     Hybrid Journal   (Followers: 3)
Recent Advances in Electrical & Electronic Engineering     Hybrid Journal   (Followers: 10)
Russian Electrical Engineering     Hybrid Journal   (Followers: 4)
SID Symposium Digest of Technical Papers     Hybrid Journal  
Simetris : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer     Open Access  
Sustainable Energy, Grids and Networks     Hybrid Journal   (Followers: 5)
Sustainable Energy, IEEE Transactions on     Hybrid Journal   (Followers: 16)
Synthesis Lectures on Electrical Engineering     Full-text available via subscription   (Followers: 2)
System analysis and applied information science     Open Access  
Telematique     Open Access  
The Scientific Bulletin of Electrical Engineering Faculty     Unknown  
Transactions on Environment and Electrical Engineering     Open Access  
Tri Dasa Mega : Jurnal Teknologi Reaktor Nuklir     Open Access  
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 6)
Wireless Engineering and Technology     Open Access   (Followers: 4)
Електротехніка і Електромеханіка     Open Access  


Journal Cover Sustainable Energy, IEEE Transactions on
  [SJR: 3.646]   [H-I: 45]   [16 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1949-3029
   Published by IEEE Homepage  [191 journals]
  • IEEE Transactions on Sustainable Energy
    • Abstract: Provides a listing of current staff, committee members and society officers.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • IEEE Transactions on Sustainable Energy
    • Abstract: Provides a listing of current committee members and society officers.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Information for Authors
    • Abstract: Provides instructions and guidelines to prospective authors who wish to submit manuscripts.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Reactive Power Control for Single-Phase Grid-Tie Inverters Using
           Quasi-Sinusoidal Waveform
    • Authors: Dong Li;Carl Ngai Man Ho;Luo Liu;Gerardo Escobar;
      Pages: 3 - 11
      Abstract: This paper presents a reactive power control technique for single-phase photovoltaic (PV) inverters, especially unfolding inverters. The proposed system retains the benefit of the unfolding inverters having low material cost and semiconductor losses, and tackles the drawback of the standard unfolding inverter not having capability of reactive power injection. It is important to note that reactive power delivery is mandatory for PV inverters according to the recent announced regulations. The concept is based on changing the shape of the grid current waveform but keeping the same zero crossing points as in the unity power factor condition. The current waveform is governed by real power and reactive power, at the price of an acceptable deformation. The operating principles of the proposed technique and mathematical derivations of the grid current function are provided in this paper. Experimental results in a grid-tie inverter prototype have shown a good agreement with the derived theory, and they confirm the feasibility of using the proposed technique in grid-tie inverters.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Harmonic Stability and Resonance Analysis in Large PMSG-Based Wind Power
    • Authors: Esmaeil Ebrahimzadeh;Frede Blaabjerg;Xiongfei Wang;Claus Leth Bak;
      Pages: 12 - 23
      Abstract: Compared to the conventional power systems, large wind power plants (WPPs) present a more challenging system, where the interactions between the passive elements and the wideband control systems of power converters may result in harmonic instability and new resonance frequencies. Most of researches about harmonic stability focus on small-scale systems, and it has not paid much attention yet to identify the mentioned resonance frequencies. This paper models and analyzes the harmonic instability and resonance frequencies in large permanent magnet synchronous generator (PMSG) based WPPs with full-scale converters, where linearized models of inner control loops of the power converters are considered. A large PMSG-based WPP introduces as a multi-input mulit-output (MIMO) control system, therefore, the stability of the whole power system is analyzed based on the real parts of the poles of the introduced MIMO system and the resonance frequencies are identified based on the element amplitudes of the MIMO matrix. An active damping controller is used to set the poles of the WPP in a desired location in order to mitigate the harmonic instability problems. Multiple case studies are provided to depict that wind turbine connections or disconnections in a WPP, as well as grid impedance variations can affect the harmonic stability and resonance frequencies. The effectiveness of the presented theoretical analysis is validated by time-domain simulations of a 400-MW WPP in PSCAD/EMTDC software environment.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • The SVC Additional Adaptive Voltage Controller of Isolated Wind-Diesel
           Power System Based on Double Sliding-Mode Optimal Strategy
    • Authors: Yang Mi;Chao Ma;Yang Fu;Chengshan Wang;Peng Wang;Poh Chiang Loh;
      Pages: 24 - 34
      Abstract: Due to the voltage fluctuation resulting from variable wind energy and reactive load change in an isolated wind-diesel hybrid system, an additional adaptive voltage compensation controller for static var compensator (SVC) by using double sliding-mode (SM) optimal strategy is proposed to maintain the system bus voltage stability. Considering the uncertainties of SVC model parameters and unobservable state variables, the SM algorithm is used to design the robust state observer and SVC adaptive voltage controller. The mathematical state model of isolated wind-diesel hybrid power system together with SVC is established, and then, the SM robust observer is constructed to estimate the SVC state variables. In order to improve the system bus voltage stability, an additional robust adaptive voltage controller is designed for SVC by selecting appropriate switching surface and adaptive reaching condition. The proposed control strategy is shown to be effective through opal-RT OP5600 simulator together with TIF28335 DSP for the isolated wind-diesel system under different operation point.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Photovoltaic-Model-Based Solar Irradiance Estimators: Performance
           Comparison and Application to Maximum Power Forecasting
    • Authors: Enrica Scolari;Fabrizio Sossan;Mario Paolone;
      Pages: 35 - 44
      Abstract: Due to the increasing proportion of distributed photovoltaic (PV) production in the generation mix, the knowledge of the PV generation capacity has become a key factor. In this paper, we propose to compute the PV plant maximum power starting from the indirectly estimated irradiance. Three estimators are compared in terms of ability to compute the PV plant maximum power, bandwidth, and robustness against measurements noise. The approaches rely on measurements of the DC voltage, current, and cell temperature, and on a model of the PV array. We show that the considered methods can accurately reconstruct the PV maximum generation even during curtailment periods, i.e., when the measured PV power is not representative of the maximum potential of the PV array. Performance evaluation is carried out by using a dedicated experimental setup on a 14.3 kWp rooftop PV installation. Results also proved that the analyzed methods can outperform pyranometer-based estimations with a simple sensing system. We show how the obtained PV maximum power values can be applied to train time series based solar maximum power forecasting techniques. This is beneficial when the measured power values, commonly used as training, are not representative of the maximum PV potential.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • A Prediction Model-Guided Jaya Algorithm for the PV System Maximum Power
           Point Tracking
    • Authors: Chao Huang;Long Wang;Ryan Shun-Cheung Yeung;Zijun Zhang;Henry Shu-Hung Chung;Alain Bensoussan;
      Pages: 45 - 55
      Abstract: This paper proposes a novel model-free solution algorithm, the natural cubic-spline-guided Jaya algorithm (S-Jaya), for efficiently solving the maximum power point tracking (MPPT) problem of PV systems under partial shading conditions. A photovoltaic (PV) system which controls the power generation with its operating voltage is considered. As the same as the generic Jaya algorithm, the S-Jaya is free of algorithm-specific parameters. A natural cubic-spline-based prediction model is incorporated into the iterative search process to guide the update of candidate solutions (operating voltage settings) in the S-Jaya and such extension is capable of improving the tracking performance. Simulation studies and experiments are conducted to validate the effectiveness of the proposed S-Jaya algorithm for better addressing PV MPPT problems considering a variety of partial-shading conditions. The performance of the proposed algorithm is benchmarked against the generic Jaya and the particle swarm optimization, which has been widely considered in the model-free MPPT, to demonstrate its advantages. Results of simulation studies and experiments demonstrate that the S-Jaya algorithm converges faster and provides a higher overall tracking efficiency.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • A New Bi-Objective Approach to Energy Management in Distribution Networks
           with Energy Storage Systems
    • Authors: Ali Azizivahed;Ehsan Naderi;Hossein Narimani;Mehdi Fathi;Mohammad Rasoul Narimani;
      Pages: 56 - 64
      Abstract: This paper introduces a novel approach for optimal operation of distribution networks at the presence of distributed generation resources and battery energy storage system. Modern power distribution networks must operate not only at the most economical way but also at a reasonable level of system reliability. Toward this end a special attention has been paid to reliability assessment in which turns the proposed problem into a multiobjective energy management (MOEM). Energy not supplied, a prominent reliability index, is considered as an objective function beside the operation cost. A hybrid evolutionary algorithm, hybrid grey wolf optimizer-particle swarm optimization algorithm, is also proposed to solve the proposed MOEM. Accuracy of the proposed algorithm is evaluated on IEEE 84-bus standard distribution system. Obtained results are compared with those available in literatures to prove the supremacy of the proposed algorithm. Furthermore, a benefit analysis has been done to assess the associated cost of the photovoltaic installment.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Performance Assessment of Wind Turbines: Data-Derived Quantitative Metrics
    • Authors: Yusen He;Andrew Kusiak;
      Pages: 65 - 73
      Abstract: Deteriorating performance of wind turbines results in power loses. A two-phase approach for performance evaluation of wind turbines is presented at past and future time intervals. Historical wind turbine data is utilized to determine the past performance, while performance at future time horizons calls for power prediction. In phase I of the proposed approach, wind power is predicted by an ensemble of extreme learning machines using parameters such as wind speed, air temperature, and the rotor speed. In phase II, the predicted power is used to construct Copula models. It has been demonstrated that the parameters of the Copula models serve as usable metrics for expressing performance of wind turbines. The Frank Copula model performs best among the five parametric models tested.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Particle Swarm Optimization Based Solar PV Array Reconfiguration of the
           Maximum Power Extraction Under Partial Shading Conditions
    • Authors: Thanikanti Sudhakar Babu;J. Prasanth Ram;Tomislav Dragičević;Masafumi Miyatake;Frede Blaabjerg;Natarajan Rajasekar;
      Pages: 74 - 85
      Abstract: For large photovoltaic power generation plants, number of panels are interconnected in series and parallel to form a photovoltaic (PV) array. In this configuration, partial shade will result in decrease in power output and introduce multiple peaks in the P-V curve. As a consequence, the modules in the array will deliver different row currents. Therefore, to maximize the power extraction from PV array, the panels need to be reconfigured for row current difference minimization. Row current minimization via Su Do Ku game theory do physical relocation of panels may cause laborious work and lengthy interconnecting ties. Hence, in this paper, an alternative to physical relocation based on particle swarm optimization (PSO) connected modules is proposed. In this method, the physical location of the modules remains unchanged, while its electrical connections are altered. Extensive simulations with different shade patterns are carried out and thorough analysis with the help of I-V, P-V curves is carried out to support the usefulness of the proposed method. The effectiveness of proposed PSO technique is evaluated via performance analysis based on energy saving and income generation. Further, a comprehensive comparison of various electrical array reconfiguration based is performed at the last to examine the suitability of proposed array reconfiguration method.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • A Nonlinear Frequency-Domain Approach for Numerical Simulation of Wave
           Energy Converters
    • Authors: Alexis Mérigaud;John V. Ringwood;
      Pages: 86 - 94
      Abstract: Nonlinear, analytical wave-energy converter (WEC) models are generally simulated through time-domain (TD) numerical integration. However, the relatively high computational requirements of TD integration are not compatible with applications where a large number of simulations are needed. Spectral domain (SD) linearization has also been proposed to take into account some nonlinear effects, while being much faster than TD integration. However, as explained in this paper, such SD models have limited accuracy, and cannot extend to the static nonlinear forces. In this paper, a nonlinear frequency-domain (NLFD) method is investigated for WEC simulation, using a projection of the dynamical equations onto a basis of trigonometric functions. A comparison with TD integration (second-order Runge$-$Kutta-RK2) and SD methods is provided, through theoretical considerations, and by means of numerical simulations based on two case studies. In the cases considered, the proposed NLFD method allows for significant computational savings compared to RK2 integration, without requiring any approximation for the radiation forces. NLFD thus shows promising potential for applications involving extensive WEC simulation, such as power production assessment, while preserving the WEC model accuracy. Although slower than SD, NLFD has significant benefits in terms of accuracy and range of applicability.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Data-Driven Correction Approach to Refine Power Curve of Wind Farm Under
           Wind Curtailment
    • Authors: Yongning Zhao;Lin Ye;Weisheng Wang;Huadong Sun;Yuntao Ju;Yong Tang;
      Pages: 95 - 105
      Abstract: Regardless of the rapid development of wind power capacity installation around the world, wind curtailment is a severe problem to be solved. Wind curtailment can cause abundant outliers and change the original characteristics of operation data in wind farms. Power curve cannot be accurately modeled with these outliers and consequently wind power forecasting as well as other applications in power system will be negatively affected. In this paper, the characteristics of the outliers caused by wind curtailment are analyzed. Then, a data-driven outlier elimination approach combining quartile method and density-based clustering method is proposed. First, the quartile method is used twice for eliminating sparse outliers. Then density-based spatial clustering of applications with noise method is applied to eliminate stacked outliers. A case study is carried out by modeling the power curves of a wind farm and 20 wind turbines in this wind farm. The accuracy of power curve modeling is significantly improved and the elimination procedure can be completed in a very short time, indicating that the proposed methods are effective and efficient for eliminating outliers. The performance of the methods is insensitive to their parameters and can be directly used in different cases without tuning parameters, both for wind turbines and wind farms.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Energetic Macroscopic Representation of a Marine Current Turbine System
           with Loss Minimization Control
    • Authors: Mahmoud R. Barakat;Boubekeur Tala-Ighil;Hicham Chaoui;Hamid Gualous;Youssef Slamani;Daniel Hissel;
      Pages: 106 - 117
      Abstract: This paper presents a detailed modeling along with an energetic macroscopic graphical representation of the marine current turbine (MCT) system. The MCT system under study consists of a 1.5-MW fixed pitch turbine, a permanent magnet synchronous generator, an ac-dc fully controlled machine side converter, a dc link, a dc-ac fully controlled grid-side converter, connection cables, a transformer, and the main grid. The control of each converter is designed by considering the tuning chain as a part of the system's energetic macroscopic representation. The machine side converter's control makes use of the maximum power point tracking torque control and the generator loss minimization (output maximization) techniques to enhance the overall efficiency when the system runs under the rated marine current speed. When the system runs above the base speed, the control mode is switched to the rated power limiting mode. The grid-side converter is controlled to stabilize the dc-link voltage within a certain range besides controlling the reactive power. The proposed control strategies are evaluated based on the model results by using the real data of The Alderney Race (Raz Blanchard in French) marine site.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Combined Economic Dispatch Considering the Time-Delay of District Heating
           Network and Multi-Regional Indoor Temperature Control
    • Authors: Chenyu Wu;Wei Gu;Ping Jiang;Zhenyuan Li;Hongyi Cai;Baoju Li;
      Pages: 118 - 127
      Abstract: Wind power consumption is often curtailed by the inflexible operation of combined heat and power (CHP) units due to the strong coupling relationship between power generation and heating supply. Besides, the time delay of district heating network and indoor temperature usually affects the operation plan of the district heating system (DHS) heavily. Hence, a practical CHP-DHS model and multiregional coordinated operation strategy based on model predictive control are developed for planning and operating this CHP system. The thermal characteristics of demand side such as the thermal inertia of buildings and thermal comfort are taken into consideration. Three types of heat source are considered: CHP units, electrical boilers, and heat storage tanks. The objective of the optimization is to minimize the overall generation costs of CHP units and conventional thermal power units. Part of real provincial power system and a municipal DHS in the Northeastern China are used in this case study. The results show that the proposed method has better performance in wind power integration and indoor temperature control.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Impacts of Wind Power Uncertainty on Grid Vulnerability to Cascading
           Overload Failures
    • Authors: Mir Hadi Athari;Zhifang Wang;
      Pages: 128 - 137
      Abstract: Higher penetration of renewables like wind power generation will introduce an unprecedented amount of uncertainty into the grid that might severely affect the grid vulnerability to cascading failures. In this study, we propose a mixed OPF-stochastic approach to analyze and simulate cascading failures in power grid and to evaluate the impact of wind generation in terms of its penetration and uncertainty level. The proposed approach incorporates both thermal stability model for transmission line outage and automatic power balance algorithms. Numerical simulation results on the IEEE 300 bus system indicate that uncertainty coming from wind energy has severe impacts on grid vulnerability to cascading overload failures under different contingency scenarios. Results also suggest that higher penetration levels of wind energy, if not managed appropriately, will add to this severity because higher uncertainties may be injected into weaker lines in a grid.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • A Fully Parallel Stochastic Multiarea Power System Operation Considering
           Large-Scale Wind Power Integration
    • Authors: Mojtaba Khanabadi;Yong Fu;Lin Gong;
      Pages: 138 - 147
      Abstract: Multiarea power system operation/coordination is used to increase the reliability of the interconnected power grids and maintain the consistency of the price across the integrated power systems. However, the implementation of this coordinated operation is facing challenges due to increase in size and complexity of the modern power systems, high penetration of the volatile renewable energy, and interdependence issues among various power systems. To address these concerns, this paper presents a fully parallel decision-making approach for the day-ahead scheduling of interconnected power systems with large-scale wind power integration while respecting the information privacy between different systems/areas. In the proposed parallel approach, each system/area solves its day-ahead scheduling problem along with its local subproblems for different wind generations' scenarios, and sends its equivalent (or processed) boundary information to other systems/areas. The proposed inter-regional coordination among systems/areas and intra-regional coordination between scenarios in each system/area will continue until the tie-line power flows and the generation outputs of generating units get converged. The modified IEEE 118-bus testing system is used in this paper to show the effectiveness of the proposed approach.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Centralized Volt–Var Optimization Strategy Considering Malicious Attack
           on Distributed Energy Resources Control
    • Authors: Ankur Majumdar;Yashodhan P. Agalgaonkar;Bikash C. Pal;Ralph Gottschalg;
      Pages: 148 - 156
      Abstract: The adoption of information and communication technology based centralized volt-var control (VVC) leads to an optimal operation of a distribution feeder. However, it also poses a challenge that an adversary can tamper with the metered data and, thus, can render the VVC action ineffective. Distribution system state estimation (DSSE) acts as a backbone of centralized VVC. Distributed energy resources (DER) injection measurements constitute leverage measurements from a DSSE point of view. This paper proposes two solutions as a volt-var optimization DSSE malicious attack mitigating strategy when the DER injection measurements are compromised. The first solution is based on local voltage regulation controller set-points. The other solution effectively employs historical data or forecast information. The concept is based on a cumulant-based probabilistic optimal power flow with the objective of minimizing the expectation of total power losses. The effectiveness of the approach is performed on the 95-bus U.K. generic distribution system and validated against Monte Carlo simulations.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Fault Prognosis and Remaining Useful Life Prediction of Wind Turbine
           Gearboxes Using Current Signal Analysis
    • Authors: Fangzhou Cheng;Liyan Qu;Wei Qiao;
      Pages: 157 - 167
      Abstract: Gearbox faults constitute a significant portion of all faults and contribute to a significant portion of the downtime of wind turbines. Thus, an accurate prediction of the gearbox remaining useful life (RUL) is important to achieve condition-based maintenance to ensure secure and reliable operations of wind turbines and reduce the cost of wind power. This, however, is a challenging work due to the lack of accurate physical degradation models and limited data. This paper proposes a new fault prognostic and RUL prediction method for gearboxes based on the adaptive neuro-fuzzy inference system (ANFIS) and particle filtering (PF) approaches. In the proposed method, the fault feature is extracted from the measured one phase stator current of the generator connected with the gearbox; the ANFIS learns the state transition function of the extracted fault feature; the PF algorithm then predicts the RUL of the gearbox based on the learned state transition function and new information of the fault feature. Experimental results on a gearbox run-to-failure test are provided to show the effectiveness of the proposed method.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Optimal Sizing and Arrangement of Tidal Current Farm
    • Authors: Yi Dai;Zhouyang Ren;Ke Wang;Wenyuan Li;Zhenwen Li;Wei Yan;
      Pages: 168 - 177
      Abstract: This paper proposes a bi-level programming-based optimization method to determine the sizing of tidal current farm (TCF) and the arrangement of tidal current turbines reaching the minimized comprehensive generation cost of tidal power. Not only the characteristics of tidal current velocity and wake effects but also the economic costs and environmental benefits brought by TCF integration are all incorporated in the proposed method. The method includes a power output model of TCF that can capture the characteristics of tidal current velocity and turbine wake effects, and a bi-level optimization model that takes into account the penalty costs of greenhouse gas emissions, the operation costs of power system, and the investment cost of tidal current turbines. The bi-level model is solved using a genetic algorithm and a quadratic programming technique. The effectiveness and adaptability of the proposed method are demonstrated using the measured data of tidal current velocity and the IEEE 30-bus test system.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Valuing Demand Response Controllability via Chance Constrained Programming
    • Authors: Kenneth Bruninx;Yury Dvorkin;Erik Delarue;William D’haeseleer;Daniel S. Kirschen;
      Pages: 178 - 187
      Abstract: Controllable loads can modify their electricity consumption in response to signals from a system operator, providing some of the flexibility needed to compensate for the stochasticity of electricity generated from renewable energy sources (RES) and other loads. However, unlike traditional flexibility providers, e.g., conventional generators and energy storage systems, demand response (DR) resources are not fully controlled by the system operator and their availability is limited by user-defined comfort constraints. This paper describes a deterministic unit commitment model with probabilistic reserve constraints that optimizes day-ahead power plant scheduling in the presence of stochastic RES-based electricity generation and DR resources that are only partially controllable, in this case residential electric heating systems. This model is used to evaluate the operating cost savings that can be attained with these DR resources on a model inspired by the Belgian power system.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Dynamic Optimal Energy Flow in the Integrated Natural Gas and Electrical
           Power Systems
    • Authors: Jiakun Fang;Qing Zeng;Xiaomeng Ai;Zhe Chen;Jinyu Wen;
      Pages: 188 - 198
      Abstract: This paper focuses on the optimal operation of the integrated gas and electrical power system with bidirectional energy conversion. Considering the different response times of the gas and power systems, the transient gas flow and steady-state power flow are combined to formulate the dynamic optimal energy flow in the integrated gas and power systems. With proper assumptions and simplifications, the problem is transformed into a single-stage linear programming to obtain the optimal operation strategy for both gas and power systems. Simulation on the test case illustrates the success of the modeling and the beneficial roles of the power-to-gas are analyzed. The proposed model can be used in the decision support for both planning and operation of the coordinated natural gas and electrical power systems.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Optimal Wind Power Uncertainty Intervals for Electricity Market Operation
    • Authors: Ying Wang;Zhi Zhou;Audun Botterud;Kaifeng Zhang;
      Pages: 199 - 210
      Abstract: It is important to select an appropriate uncertainty level of the wind power forecast for power system scheduling and electricity market operation. Traditional methods hedge against a predefined level of wind power uncertainty, such as a specific confidence interval or uncertainty set, which leaves the questions of how to best select the appropriate uncertainty levels. To bridge this gap, this paper proposes a model to optimize the forecast uncertainty intervals of wind power for power system scheduling problems, with the aim of achieving the best trade-off between economics and reliability. Then, we reformulate and linearize the models into a mixed integer linear programming (MILP) without strong assumptions on the shape of the probability distribution. In order to invest the impacts on cost, reliability, and prices in a electricity market, we apply the proposed model on a two-settlement electricity market based on a six-bus test system and on a power system representing the U.S. state of Illinois. The results show that the proposed method can not only help to balance the economics and reliability of the power system scheduling, but also help to stabilize the energy prices in electricity market operation.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Stochastic Optimal Planning of Battery Energy Storage Systems for Isolated
    • Authors: Hisham Alharbi;Kankar Bhattacharya;
      Pages: 211 - 227
      Abstract: A novel stochastic planning framework is proposed to determine the optimal battery energy storage system (BESS) capacity and the year of installation in an isolated microgrid using a new representation of the BESS energy diagram. The BESS enhances microgrid operation via load leveling and reserve provisions in conjunction with the spinning reserve from dispatchable distributed generation (DG) units. A decomposition-based approach is proposed to solve the problem of stochastic planning of BESS under uncertainty. The optimal decisions minimize the net present value (NPV) of total expected costs over a multiyear horizon taking into consideration the optimal BESS operation considering a novel matrix representing BESS energy capacity degradation. The proposed approach is solved in two stages as mixed-integer linear programming problems to ensure the convergence of the stochastic optimization problem. The optimal ratings of the BESS are determined in the first stage, while the optimal installation year is determined in the second stage. The approach ensures utilizing the allocated budget effectively by performing several iterations. Extensive studies considering four types of BESS technologies for deterministic, Monte Carlo Simulations, and stochastic cases are presented to demonstrate the effectiveness of the proposed approach.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Reducing Curtailed Wind Energy Through Energy Storage and Demand Response
    • Authors: Hamideh Bitaraf;Saifur Rahman;
      Pages: 228 - 236
      Abstract: Curtailed wind energy is a challenge in utilities with high wind energy penetration. This happens mainly when wind generation exceeds load minus the minimum stable operating point of generation units. At first, the role of generation mix on the curtailed wind energy is analyzed. Then, demand response (DR) applications are modeled to quantify additional reductions in the curtailed wind energy. The uniqueness of this approach is that the impact of the DR rebound effect on the system load shape can be directly reflected. This allows scheduling of DR such that the rebound period (higher demand) aligns itself with high wind output period. This minimizes the need for curtailment. Next, the issue of charging/discharging different large-scale energy storage technologies (e.g., compressed air energy storage, pumped hydro energy storage, and batteries) is addressed. This allows their impact on wind curtailment to be analyzed in detail. Finally, various combinations of energy storage and DR options are considered for investigating their impacts on further reducing wind curtailments. This problem is formulated as a mixed integer linear programming using wind and load data from Bonneville Power Administration.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Optimal Sizing for Grid-Tied Microgrids With Consideration of Joint
           Optimization of Planning and Operation
    • Authors: Jian Chen;Weitong Zhang;Jiaqi Li;Wen Zhang;Yutian Liu;Bo Zhao;Yicheng Zhang;
      Pages: 237 - 248
      Abstract: This paper presents a multiobjective optimization method to jointly optimize the planning and operation of a grid-tied microgrid (MG) with various distributed generation sources such as wind turbine and photovoltaic arrays with the assistance of demand side management. In order to explore the economy and demand variety, the problem is formulated as a double-objective optimization to minimize the total annual cost and to maximize the customer satisfaction. To solve the multiobjective optimization problem, a fuzzy satisfaction-maximizing method is adopted to convert the original problem into a single objective optimization problem and a mixed integer linear programming algorithm is then used to solve the problem. To verify the proposed solution, various case studies have been carried out and compared. The results show that the proposed method is effective in minimizing the cost of an MG without sacrificing the satisfaction of customers.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • An Analytical Approach to Evaluate the Reliability of Offshore Wind Power
           Plants Considering Environmental Impact
    • Authors: Biyang Wang;Xifan Wang;Xiuli Wang;Chengcheng Shao;Paul D. Judge;Tim C. Green;
      Pages: 249 - 260
      Abstract: The accurate quantitative reliability evaluation of offshore wind power plants (OWPPs) is an important part in planning and helps us to obtain economic optimization. However, loop structures in collector systems and large quantities of components with correlated failures caused by shared ambient influences are significant challenges in the reliability evaluation. This paper proposes an analytical approach to evaluate the reliability of OWPPs considering environmental impact on failures and solve the challenges by protection zone models, equivalent power unit models, and common cause failure (CCF) analysis. Based on the investigation of the characteristics of OWPP and related failures mechanisms, the components are divided into three CCF subsets. With the aid of the protection zone model and equivalent power unit model merged with CCF, the faulty collector system state evaluation is applied to reduce the computational burden. The case studies present the necessity and improved performance of merging CCF analysis into modeling via the comparison with other two simplified methods. A sensitivity analysis is also carried out to account for inaccuracy of failure data. The results show that the assumption of independent failures in the conventional method might lead to over-optimistic or over-pessimistic evaluation depending on the CCF style.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Statistical Representation of Wind Power Ramps Using a Generalized
           Gaussian Mixture Model
    • Authors: Mingjian Cui;Cong Feng;Zhenke Wang;Jie Zhang;
      Pages: 261 - 272
      Abstract: Wind power ramps are significantly impacting the power balance of the system operations. Understanding the statistical characteristics of ramping features would help power system operators better manage these extreme events. Toward this end, this paper develops an analytical generalized Gaussian mixture model (GGMM) to fit the probability distributions of different ramping features. The nonlinear least-squares method with the trust-region algorithm is adopted to optimize the tunable parameters of mixture components. The optimal number of mixture components is adaptively solved by minimizing the Euclidean distance between the GGMM and the actual histogram distribution. The probability distribution of ramping features is generally truncated due to the ramp definition with a specific threshold. Thus, a sign function is utilized to truncate the GGMM distribution. Then, the cumulative distribution function of the GGMM is analytically derived and utilized to design a random number generator for ramping features. Numerical simulations on publicly available wind power data show that the parametric GGMM can accurately characterize the irregular and multimodal distributions of ramping features.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Optimal Stochastic Operation of Integrated Low-Carbon Electric Power,
           Natural Gas, and Heat Delivery System
    • Authors: Yong Li;Yao Zou;Yi Tan;Yijia Cao;Xindong Liu;Mohammad Shahidehpour;Shiming Tian;Fanpeng Bu;
      Pages: 273 - 283
      Abstract: Integrated energy system is important for the high-efficient utilization of multitype energy systems. In this paper, the stochastic optimal operation is investigated for the micro integrated electric power, natural gas, and heat delivery system (IPGHS). First, a low-carbon micro-IPGHS is proposed with the comprehensive consideration of renewable generation, carbon-capture-based power-to-gas technology, and the combined power and heat units. Second, a scenario-based optimal operation model for micro-IPGHS is proposed to handle uncertainties in energy demand and renewable generation. In the proposed model, energy transactions between micro-IPGHS and upstream energy systems as well as constraints for battery storage, natural gas storage, and heat storage systems are considered. Finally, a case study is used for the proposed low-carbon micro-IPGHS to validate the optimal stochastic operation approach. The proposed integrated system can effectively utilize the variable clean energy for optimizing the delivery of the green operation in micro-IPGHS.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • A Return on Investment Model for the Implementation of New Technologies on
           Wind Turbines
    • Authors: Roozbeh Bakhshi;Peter A. Sandborn;
      Pages: 284 - 292
      Abstract: Renewable energy from wind and solar is considered to be the main alternative to fossil fuels. The costs of renewable energy technologies are high and without tax credits they are not currently competitive with fossil fuels in many markets. Improvements in the performance or reduction in operational costs will have significant impacts on the price of renewable energy and ultimately impact their competitiveness. New technologies targeted at improving the efficiency of the current systems or reducing their life-cycle costs will help; however, these technologies are expensive and detailed cost tradeoff and return on investment (ROI) analysis are required to make business cases for them. In this paper, we formulate an ROI model and describe its implementation in a stochastic discrete-event simulator to calculate financial tradeoffs and enable business cases for technology insertion into wind farms. The new ROI model includes changes in revenue and operations costs (including changes in reliability due to the technology insertion) and introduces the concept of identical timeline conditions to guarantee a meaningful ROI calculation. A case study for using light detection and ranging (LIDAR) to increase the efficiency and improve the reliability of wind turbines in a wind farm is provided.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Calculating Steady-State Operating Conditions for DFIG-Based Wind Turbines
    • Authors: Meng Wu;Le Xie;
      Pages: 293 - 301
      Abstract: This paper proposes a noniterative approach to calculate steady-state operating conditions of doubly fed induction generator (DFIG)-based wind turbines. The proposed approach can be applied to calculate steady-state operating conditions for the full-order dynamic model of DFIG-based wind turbines under d-q reference frame. Lossy DFIG back-to-back converters can be well supported, and nonzero reactive power delivery through DFIG grid-side converters can be handled. This noniterative approach encounters no convergence issues, which guarantees fast computation speed. It provides analytical solutions to the steady-state operating conditions of DFIG-based wind turbines. The proposed method could potentially be applied to obtain steady-state operating conditions before performing eigenvalue analysis and electromagnetic simulations for wind farms. Simulations performed on a single-machine-infinite-bus test system and a multibus test system verify the effectiveness of the proposed method.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Frequency Response Constrained Modified Interval Scheduling Under Wind
    • Authors: Vivek Prakash;Kailash Chand Sharma;Rohit Bhakar;Har Pal Tiwari;Furong Li;
      Pages: 302 - 310
      Abstract: Large wind generation in existing power system increases the requirement of frequency response (FR) services, as the existing wind generators are weak in providing inertial and primary FR (PFR). This necessitates optimal PFR schedules from unit commitment (UC). PFR constrains have been considered in Stochastic UC problem. However, the simulation process is computationally demanding and necessitates a modeling technique with minimal computational burden, to optimize generation and PFR schedules simultaneously, considering wind uncertainty. This paper proposes computationally fast modified interval UC (MIUC) model to minimize the generation scheduling cost and optimize PFR. Uncertainty is modeled using upper and lower limit, while ramp requirements of consecutive hours depend on the net load scenarios. Case studies are carried out on a single area IEEE RTS; comparative analysis with stochastic scheduling technique show that the proposed method can drastically reduce the simulation time, while offering similar level of operating PFR cost, and PFR schedules, thus addressing wind uncertainty at different penetration level adequately. Further, the proposed model has the potential to offer solutions within acceptable operational time frames for the PFR ancillary service market clearing and dispatch for future low carbon systems.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Partially Decoupled Adaptive Filter Based Multifunctional Three-Phase GPV
    • Authors: Vedantham Lakshmi Srinivas;Shailendra Kumar;Bhim Singh;Sukumar Mishra;
      Pages: 311 - 320
      Abstract: This paper deals with partially decoupled adaptive Volterra filter (PDAVF) based control for a three-phase two-stage grid-interfaced photovoltaic (GPV) system. Besides maximum power extraction, the proposed control is having the potential of grid currents balancing, harmonics currents mitigation, reactive power compensation, and adaptive adjustment of DC bus voltage. The control technique is efficient in extraction of weight component of reference grid currents and an adaptation routine of filter weights uses the principle of fifth-order PDAVF with single-element observation vector implemented by using the method of least mean squares (LMS). An increased order of partial filter assures accurate estimation of filter weights by adaptive weight update at each filter step. The convergence is ensured by providing bounds on algorithm's step size. The algorithm overcomes drawbacks of Adaline-based LMS and LMF (least mean fourth) based weight estimations without imposing high computational burden. The switching losses in voltage source converter are minimized using adaptive DC bus voltage. Effectiveness of PDAVF is presented through simulation and test results. These results are found satisfactory with improved steady state and dynamic performances and total harmonic distortion of grid currents meet an IEEE-519 standard.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Influence of the Wake Effect on Electrical Dynamics of Commercial Tidal
           Farms: Application to the Alderney Race (France)
    • Authors: Ottavio A. Lo Brutto;Mahmoud R. Barakat;Sylvain S. Guillou;Jérôme Thiébot;Hamid Gualous;
      Pages: 321 - 332
      Abstract: Marine renewable energies (MRE) allow the diversification of the energy mix and are thus developing rapidly. The extraction of tidal energy is one of the most promising MRE and is nowadays in a preindustrial phase. The Alderney Race (Raz Blanchard in French), situated between the island of Alderney (Channel Islands) and the Cap de la Hague in France, capitalizes a resource estimated between 5 and 14 TWh/year. This great tidal resource attracts tidal energy developers. Harnessing the high potential of the Alderney Race requires deploying numerous turbines in arrays. The purpose of this paper is to investigate the influence of the wake effects on the electrical dynamics of commercial tidal farms. The proposed methodology is applied to a hypothetical tidal farm in the Alderney Race. The influence of the wake effects on the power produced by a tidal farm is assessed by comparing simulations where the effect is neglected to simulations with wake effects. Two operational conditions are analyzed: Normal operation (one-day simulation with varying tidal speed); grid disturbances (voltage dip at the tidal farm point of common coupling). Simulations show that neglecting the wake effect implies significant errors in active power estimation at the point of common coupling during normal operation. Moreover, differences in the behavior of the system during voltage dip occur if the wake effect is not taken into account.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Mitigation Measures for Photovoltaics Retrofit
    • Authors: Karel Máslo;Andrew Kasembe;
      Pages: 333 - 339
      Abstract: An increased penetration of distributed energy sources in Europe causes challenges in the power system operation. One of these is the so-called 50.2 Hz issue-A threat to frequency stability due to disconnection of a large amount of distributed sources especially photovoltaic modules at the same time. This paper analyzes the frequency stability of the continental Europe synchronous area from the above-mentioned perspective using two dynamic models: Single-node and multinode. The influence of the system parameters (such as inertia and load) is demonstrated using the single-node model. The influence of local and interarea frequency oscillations on renewable energy sources disconnections is analyzed using the multinode model.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Intrahour Cloud Tracking Based on Probability Hypothesis Density Filtering
    • Authors: Florian Barbieri;Corentin Rifflart;Ba-Tuong Vo;Sumedha Rajakaruna;Arindam Ghosh;
      Pages: 340 - 349
      Abstract: Swift variations in the cloud cover may cause significant power output fluctuations in solar power systems, jeopardizing power quality. Forecasting the power output with a very short horizon below 30 s can be seen as a cloud cover forecasting problem solved by processing images from a sky camera. After a preprocessing stage that identifies clouds with a criterion based on the red-green blue values of each pixel, a probability hypothesis density filter or a more advanced cardinalized probability hypothesis density filter can be used to an unknown and varying number of clouds. The time when cumulus clouds will shade the sun can be forecasted with an absolute precision 6 s ahead and with an acceptable accuracy 27 s ahead. It has been found that both filters are equally well suited for a real-time online nowcasting application. They also have the potential to deal with noise and the swift dynamics and high variability of clouds.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Optimal Cell-to-Cell Balancing Topology Design for Serially Connected
           Lithium-Ion Battery Packs
    • Authors: Quan Ouyang;Jian Chen;Jian Zheng;Huazhen Fang;
      Pages: 350 - 360
      Abstract: A battery pack can see energy imbalance among its cells resulting from cell-to-cell variation in capacity, internal resistance, and other parameters. Its successful and safe operation thus necessitates dynamic energy equalizing to adjust each cell's state-of-charge to the same level. The cell equalizing system for a serially connected battery pack is modeled as a multiagent system here. A consensus-based state-of-charge equalizing algorithm is proposed with its convergence proved through theoretical analysis. Following this development, an interesting and important problem is investigated: how to add extra individual cell equalizers or edges to the original cell equalizing system's topology to maximally accelerate the equalizing process. It is found that the balancing time depends on the algebraic connectivity of the topology graph, which is measured by the second smallest eigenvalue of the graph's Laplacian matrix. Then, a combinatorial 0-1 optimization problem is formulated and addressed to optimally choose added edges that lead to the maximum increase in the algebraic connectivity. The proposed results are validated through simulation and experiments, which demonstrate that the balancing time can be significantly reduced by just adding one optimal individual cell equalizer to the original cell equalizing system.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Modeling and Integration of Flexible Demand in Heat and Electricity
           Integrated Energy System
    • Authors: Changzheng Shao;Yi Ding;Jianhui Wang;Yonghua Song;
      Pages: 361 - 370
      Abstract: This paper is focused on utilizing customers' flexible energy demand, including both heat demand and electricity demand, to provide balancing resources and relieve the difficulties of integrating variable wind power with the combined heat and power. The integration of heat and electricity energy systems providing customers with multiple options for fulfilling their energy demand is described. Customer aggregators are introduced to supply downstream demand in the most economical way. Controlling customers' energy consumption behaviors enables aggregators to adjust their energy demand in response to supply conditions. Incorporating aggregators' flexible energy demand into the centralized energy dispatch model, a two-level optimization problem (TLOP) is first formed where the system operator maximizes social welfare subject to aggregators' strategies, which minimize the energy purchase cost. Furthermore, the subproblems are linearized based on several reasonable assumptions. Optimal conditions of the subproblems are then transformed as energy demands to be described as explicit piecewise-linear functions of electricity prices corresponding to the demand bid curves. In this way, the TLOP is transformed to a standard optimization problem, which requires aggregators to only submit a demand bid to run the centralized energy dispatch program. All the parameters pertaining to the aggregators' energy consumption models are internalized in the bid curves. The proposed technique is illustrated in a modified testing system.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • A New Smooth Synchronization of Brushless Doubly-Fed Induction Generator
           by Applying a Proposed Machine Model
    • Authors: Ramtin Sadeghi;Seyed M. Madani;Mohammad Ataei;
      Pages: 371 - 380
      Abstract: The Brushless Doubly-Fed induction Generator (BDFG) has a commercial potential for wind power generation, due to its low maintenance cost. For simplicity, the Cascaded Brushless Doubly Fed induction Generator (CBDFG) topology is usually applied as a model for BDFG. The BDFG-based wind turbines must be synchronized and connected to the grid, without inrush current. This paper purposes an improved Direct Torque Control (DTC) method for smooth synchronization of BDFG. Since BDFG has a complicated model, due to the resistance and voltage source in its rotor loop, finding proper references for smooth synchronization is difficult. To overcome this difficulty, a new model for BDFG is proposed. Appropriate flux and torque references for the DTC scheme are proposed based on this model, in order to achieve grid synchronization without inrush current. A 2-MW BDFG is simulated to show the efficiency and accuracy of this proposed method. The experimental results of a 3-kW laboratory scale BDFG confirm the efficiency of this proposed method.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Bacterial Foraging Optimization Approach to Parameter Extraction of a
           Photovoltaic Module
    • Authors: Bidyadhar Subudhi;Raseswari Pradhan;
      Pages: 381 - 389
      Abstract: This paper presents a new parameter extraction method for photovoltaic (PV) modules exploiting Bacterial Foraging Optimization (BFO) technique. In a PV system, validation of the model of a PV module with correctly chosen parameters is essential. An efficient parameter extraction method is required to estimate the parameters of PV module. Although, a number of parameter extraction methods are available in literature but there is a need to explore parameter extraction methods that could extract globally optimized parameters in changing weather conditions. One of the recent evolutionary computing approaches called BFO exhibits global optimization performance. Therefore, we employ BFO for extraction of parameters of a PV module. The proposed BFO-based parameter extraction method has been tested for different types of PV modules at different test conditions. Analyzing both the simulation and experimental results obtained using BFO; it is found that the module parameters are more accurate compared to that of Newton-Raphson, particle swarm optimization, and enhanced simulated annealing methods.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Solar PV-Based Scalable DC Microgrid for Rural Electrification in
           Developing Regions
    • Authors: Mashood Nasir;Hassan Abbas Khan;Arif Hussain;Laeeq Mateen;Nauman Ahmad Zaffar;
      Pages: 390 - 399
      Abstract: In this paper, we detail the design, analysis, and implementation of a highly distributed off-grid solar photovoltaic dc microgrid architecture suitable for rural electrification in developing countries. The proposed architecture is superior in comparison with existing architectures for rural electrification because of its 1) generation and storage scalability, 2) higher distribution efficiency (because of distributed generation and distributed storage for lower line losses), 3) ability to provide power for larger communal loads without the requirement for large, dedicated generation by extracting the benefit of usage diversity, and 4) localized control by using the hysteresis-based voltage droop method, thus eliminating the need for a central controller. The proposed microgrid architecture consists of several nanogrids capable of the self-sustained generation, storage, and bidirectional flow of power within the microgrid. Bidirectional power flow and distributed voltage droop control are implemented through the duty cycle control of a modified flyback converter. A detailed analysis in terms of power flow, loss, and system efficiency was conducted by using the Newton-Raphson method modified for dc power flow at varying distribution voltages, conductor sizes, and schemes of interconnection among the contributing nanogrids. A scaled-down version of the proposed architecture with various power sharing scenarios was also implemented on hardware, and yielded satisfactory results.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Probabilistic Stability Analysis of Subsynchronous Resonance for
           Series-Compensated DFIG-Based Wind Farms
    • Authors: Wuhui Chen;Xiaorong Xie;Danhui Wang;Huakun Liu;Hui Liu;
      Pages: 400 - 409
      Abstract: The wind speed of high uncertainty has an important impact on the emerging subsynchronous resonance (SSR) caused by the interaction between doubly-fed induction generator (DFIG)-based wind farms and series-compensated transmissions. This paper proposes a piecewise probabilistic collocation method (PPCM) for assessing the probabilistic stability of SSR in terms of the random wind speed. The PPCM can tackle the inherent nonlinearity resulting from the switching among different operational modes of DFIG. Using the proposed PPCM, the more accurate probability density function (PDF) of the damping can be obtained with a small computation burden. Furthermore, for the probabilistic stability assessment of SSR, this paper also develops the Weibull probabilistic model of the wind speed using the two-year statistical data. The results obtained with the proposed method show consistence with those of the Monte Carlo method (MCM). Finally, field data of SSR events in the practical wind farms are also presented to validate the effectiveness of the proposed method and its produced results.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Electric Vehicle Scheduling Considering Co-optimized Customer and System
    • Authors: Maigha;Mariesa L. Crow;
      Pages: 410 - 419
      Abstract: Efficient electric vehicle (EV) scheduling is a multi-objective optimization problem with conflicting customer and system operator interests, especially during vehicle-to-grid implementations. Economic charging while minimizing battery degradation and maintaining system load profiles couple the interests of these two entities. This paper focuses on identifying the relationships between these objectives and proposes to use an augmented epsilon-constrain (AUGMECON) based technique to implement two-way and three-way multi-objective optimizations. The importance of using these objectives in peak-shaving and valley-filling for an aggregated (residential) EV fleet is discussed. The proposed solution provides a look-ahead strategy into effective EV scheduling by co-optimizing multiple objectives. To provide operational guidance to utilities and customers, an optimal solution may be selected from those represented by the Pareto fronts.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Identification of Critical Switches for Integrating Renewable Distributed
           Generation by Dynamic Network Reconfiguration
    • Authors: Shunbo Lei;Yunhe Hou;Feng Qiu;Jie Yan;
      Pages: 420 - 432
      Abstract: With growing penetration of renewable distributed generations (DGs) in distribution systems, effective integration of DGs has become a major concern. Distribution system dynamic reconfiguration (DSDR), which relies on real-time operations of remote-controlled switches, is potentially an efficient strategy receiving inadequate attention. Moreover, in most DSDR-related publications, normally all switches are assumed remotely controllable, which is not practical. Here we borrow the concept of critical switches to denote the switches that are most effective in accommodating DGs by DSDR. In this regard, the problem of identifying critical switches is not well investigated, although in several related publications, selected switches are assumed remote-controlled based on experience. In this work, we study the application of DSDR for DG integration. Critical switches, which optimally enable intra-day DSDR to minimize DG curtailments, are identified by limiting the number of switches to be operated and the switch-type-dependent operation constraints. Considering uncertainties of loads and DGs, the problem is formulated as a two-stage robust optimization model solved by a nested column-and-constraint generation algorithm. Illustrative cases show that DG curtailments can be significantly reduced by a small number of critical switches that operate only several times in intra-day DSDR. The proposed method can be used to provide insights for switch allocation, maintenance, and operation.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Control Strategies for Point Absorbers Considering Linear Generator Copper
           Losses and Maximum Excursion Constraints
    • Authors: Antonio de la Villa-Jaén;Dan El Montoya-Andrade;Agustín García-Santana;
      Pages: 433 - 442
      Abstract: Among the different available wave energy extraction technologies, point absorber converters that use a linear direct-drive generator represent a promising alternative. Evidence of this can be found in the different prototypes that have been widely tested in recent years. As in other technologies, the control strategy that governs the power take-off system largely determines the overall-efficiency and the dynamic behavior of the oscillating system. It is advisable to consider the copper losses in the electric generator when assessing the overall performance of each strategy, as they could significantly affect the overall efficiency of the system. On the other hand, it is expedient to manage properly the energy dissipated in the end-stops that limit the maximum displacement of the oscillating system in high waves. This paper presents two reactive and latching control strategies whose novelty is to consider simultaneously the copper losses reduction in the electric generator and the limitation of the maximum excursion constraints of the oscillating system in order to extract more energy from waves. In addition, these control strategies are compared with conventional techniques. The results of the numerical simulations allow researchers to analyze the performance of the strategies from different perspectives.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Distributed Agent Consensus-Based Optimal Resource Management for
    • Authors: Tianqiao Zhao;Zhengtao Ding;
      Pages: 443 - 452
      Abstract: This paper considers the optimal resource management problem for microgrids. Microgrids provide a promising approach to fulfil challenges of the integration of distributed renewable generations and energy storage systems. However, the resource management in a microgrid encounters the new difficulty, i.e., supply-demand imbalance, caused by the intermittence of renewable sources. Therefore, an optimal solution is proposed to the resource management by enhancing the communication and coordination under a multiagent system framework. An agent is a participant, for instance, the distributed renewable generator/energy storage system of the microgrid. With this multiagent system, the distributed optimal solution only utilizes the local information, and interacts with the neighboring agents. Thus, single-node congestion is avoided since the requirement for a central control center is eliminated, and it is robust against single-link/node failures. The analysis will show that the proposed solution can solve the resource management problem in an initialization-free manner. Additionally, the proposed strategy can maintain the supply-demand balance under a time-varying supply-demand deviation. The simulation studies are carried out for IEEE 14-bus and 162-bus power systems to validate the effectiveness of the proposed distributed solution.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Nonlinear Modeling and Verification of a Heaving Point Absorber for Wave
           Energy Conversion
    • Authors: Bingyong Guo;Ron Patton;Siya Jin;James Gilbert;Dan Parsons;
      Pages: 453 - 461
      Abstract: Although the heaving point absorber (PA) concept is well known in wave energy conversion research, few studies focus on appropriate modeling of nonlinear fluid viscous and mechanical friction dynamics. Even though these concepts are known to have nonlinear effects on the hydrodynamic system, most research studies consider linearity as a starting point and in doing so have a weak approach toward modeling the true dynamic behavior, particularly close to resonance. The sole use of linear modeling leads to limited ability to develop control strategies capable of true power capture optimization and suitable device operation. Based on a 1/50 scale cylindrical heaving PA, this research focuses on a strategy for hydrodynamic model development and experimental verification. In this study, nonlinear dynamics are considered, including the lumped effect of the fluid viscous and mechanical friction forces. The excellent correspondence between the derived nonlinear model and wave tank tested PA behaviors provides a strong background for wave energy tuning and control system design.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • A Non-Sequential Probabilistic Production Simulation Method for Wind
           Energy Curtailment Evaluation Considering the Seasonal Heat Supply
    • Authors: Haibo Li;Zongxiang Lu;Ying Qiao;Ningbo Wang;
      Pages: 462 - 473
      Abstract: High wind energy curtailment during winter and early spring in north China has drawn widespread concern in recent years, which, at source, results from the incongruous planning between wind power development and other generation expansion. However, the scenarios obtained by traditional planning method without considering the seasonal heat supply constraints are far from the actual operation stage. More difficulty lies in the lack of sequential data of wind power and load demand in planning stage. A nonsequential probabilistic production simulation model is proposed to evaluate the wind energy curtailment during the heat supply period, which only needs the input data of the cumulative probability function (CDF) and/or probability density function (PDF) of heat demand, electricity demand, and wind power. Then an algorithm based on the equivalent joint energy function and minimal power-heat ratio method is applied to solve the model. The simulations have been performed based on the actual data of a large wind power zone in north China. Comparing with the previous sequential simulation method, the precision of the proposed method is satisfactory and the calculation time is dramatically reduced.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Enhanced Voltage Control of VSC-HVDC-Connected Offshore Wind Farms Based
           on Model Predictive Control
    • Authors: Yifei Guo;Houlei Gao;Qiuwei Wu;Haoran Zhao;Jacob Østergaard;Mohammad Shahidehpour;
      Pages: 474 - 487
      Abstract: This paper proposes an enhanced voltage control strategy (EVCS) based on model predictive control (MPC) for voltage-source-converter-based high-voltage direct-current (VSC-HVDC)-connected offshore wind farms (OWFs). In the proposed MPC-based EVCS, all wind turbine generators (WTGs) and the wind-farm-side VSCs are optimally coordinated to keep voltages within the feasible range and reduce system power losses. Considering the high R/X ratio of the OWF collector system, the effects of active power outputs of WTGs on voltage control are also taken into consideration. The predictive model of the VSC with a typical cascaded control structure is derived in detail. The sensitivity coefficients are calculated by an analytical method to improve the computational efficiency. A VSC-HVDC-connected OWF with 64 WTGs was used to validate the proposed voltage control strategy.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • An Explanation of Oscillations Due to Wind Power Plants Weak Grid
    • Authors: Lingling Fan;Zhixin Miao;
      Pages: 488 - 490
      Abstract: An existing wind power plant at ERCOT experienced poorly damped and undamped voltage oscillations under weak grid conditions. The oscillations became worse during high power outputs. This letter aims to find the root cause of such oscillations. Our research provides a linearized system model by combining the vector control of wind power plants and the weak grid interconnection. Using this model, this letter succeeds in explaining that the weak grid condition introduces a zero in right half plane for the open-loop system, which can lead to poorly damped or undamped oscillations.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Variable Droop Voltage Control For Wind Farm
    • Authors: Yujun Li;Zhao Xu;Jianliang Zhang;Ke Meng;
      Pages: 491 - 493
      Abstract: Converters of variable speed wind turbines in a wind power plant may possess different levels of reactive power capacity under variable power generation of each WT due to wake effects. This letter proposes a variable droop gain control scheme that seeks to mitigate voltage fluctuations at point of common coupling (PCC) by fully utilizing the voltage regulation capability of each WT converter. Droop gain of voltage controller in each WT converter is adaptively adjusted based on its current maximum reactive power capacity so that WT converters at back rows that have higher reactive power capacity can contribute more to PCC voltage regulation.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • Introducing the IEEE PES Resource Center
    • Pages: 494 - 494
      Abstract: Advertisement, IEEE.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • I am investing in tomorrow Are you'
    • Pages: 495 - 495
      Abstract: Advertisement, IEEE.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
  • The Power of Information
    • Pages: 496 - 496
      Abstract: Advertisement, IEEE.
      PubDate: Jan. 2018
      Issue No: Vol. 9, No. 1 (2018)
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