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  Subjects -> ENGINEERING (Total: 2383 journals)
    - CHEMICAL ENGINEERING (204 journals)
    - CIVIL ENGINEERING (199 journals)
    - ELECTRICAL ENGINEERING (109 journals)
    - ENGINEERING (1248 journals)
    - ENGINEERING MECHANICS AND MATERIALS (396 journals)
    - HYDRAULIC ENGINEERING (56 journals)
    - INDUSTRIAL ENGINEERING (74 journals)
    - MECHANICAL ENGINEERING (97 journals)

ELECTRICAL ENGINEERING (109 journals)                     

Showing 1 - 109 of 109 Journals sorted alphabetically
3C TIC     Open Access   (Followers: 1)
Actuators     Open Access   (Followers: 4)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 5)
Advances in Electrical Engineering     Open Access   (Followers: 26)
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)
Bulletin of Electrical Engineering and Informatics     Open Access   (Followers: 8)
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)
Current Trends in Signal Processing     Full-text available via subscription   (Followers: 5)
Edu Elektrika Journal     Open Access  
Electric Power Components and Systems     Hybrid Journal   (Followers: 7)
Electric Power Systems Research     Partially Free   (Followers: 19)
Electrical and Electronic Engineering     Open Access   (Followers: 33)
Electrical and Power Engineering Frontier     Open Access   (Followers: 26)
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: 84)
IEEE Electrical Insulation Magazine     Full-text available via subscription   (Followers: 43)
IEEE Signal Processing Magazine     Full-text available via subscription   (Followers: 76)
IEEE Transactions on Control of Network Systems     Hybrid Journal   (Followers: 13)
IEEE Transactions on Dielectrics and Electrical Insulation     Hybrid Journal   (Followers: 16)
IEEE Transactions on Signal and Information Processing over Networks     Full-text available via subscription   (Followers: 11)
IEEJ Transactions on Electrical and Electronic Engineering     Hybrid Journal   (Followers: 16)
IET Control Theory & Applications     Hybrid Journal   (Followers: 23)
IET Electric Power Applications     Hybrid Journal   (Followers: 27)
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  
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: 23)
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: 3)
International Journal of Nuclear Security     Open Access   (Followers: 1)
International Journal of Turbomachinery, Propulsion and Power     Open Access   (Followers: 5)
International Journal on Communication     Full-text available via subscription   (Followers: 12)
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: 21)
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering     Open Access   (Followers: 28)
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 Pendidikan Teknik Elektro Undiksha     Open Access  
Jurnal Rekayasa Elektrika     Open Access  
Jurnal Teknik Elektro dan Komputer     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: 19)
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: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • IEEE Transactions on Sustainable Energy
    • Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Information for Authors
    • Abstract: These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Evaluation of Economic Benefits of DER Aggregation
    • Authors: Georgia E. Asimakopoulou;Nikos D. Hatziargyriou;
      Pages: 499 - 510
      Abstract: The penetration of distributed energy resources (DER), including distributed generators and flexible demand, is increasing worldwide and is expected to increase further encouraged by environmental policies and decreasing costs. Due to their large number and spatial dispersion, DER's effective integration into the operation of electricity markets is a complex and demanding task. Moreover, their relatively small size makes their direct individual participation in the electricity market, although theoretically possible, highly impractical. This paper aims to quantify the benefits of the aggregated participation of DER in the electricity market via a DER Aggregator. The DER Aggregator's interactions with his customers and with the wholesale market are modeled as a bilevel programming problem: the upper level describes the DER Aggregator decision-making; the lower level encompasses the DERs' decision model and the market clearing process. Several scenarios are examined in order to draw general conclusions regarding the conditions under which DER aggregation is beneficial for DER owners and the aggregator.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • An Autonomous Real-Time Charging Strategy for Plug-In Electric Vehicles to
           Regulate Frequency of Distribution System With Fluctuating Wind Generation
           
    • Authors: Shiwei Xia;S. Q. Bu;Xiao Luo;Ka Wing Chan;Xi Lu;
      Pages: 511 - 524
      Abstract: Plug-in electric vehicles (PEVs) could provide valuable ancillary service for power systems with intermittent renewables. This paper proposes a charging model of a large amount of PEVs to mitigate the high-level wind power fluctuations in a distribution network so as to regulate system frequency. With the prerequisite that all PEV daily driving patterns are completely satisfied, the PEV charging power is economically allocated to counterbalance the wind generation intermittency. Afterward, a center-free control scheme based on the consensus algorithm is designed for PEVs to share the fluctuating wind generation in a fully distributed manner. The scheme is robust and flexible to practical PEV charging behaviors including arrival and departure time, initial and desired SOC, as well as the frequently changed departure time. Comprehensive simulations on a distribution system with coal and diesel generators, several wind farms and 2000 PEVs demonstrate that the proposed PEV charging scheme could effectively regulate the system frequency in the real time while the PEV users' charging requirements could be flexibly satisfied.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Decentralized Optimal Servo Control System for Implementing Instantaneous
           Reactive Power Sharing in Microgrids
    • Authors: Mohsen Eskandari;Li Li;Mohammad H. Moradi;
      Pages: 525 - 537
      Abstract: Active power is dispatched among distributed generation (DG) units in microgrids (MG) by means of f/P droop control loop, which controls the frequency set-point of voltage source converter (VSI). Since the frequency is a global variable, active power sharing is implemented well proportional to droop coefficients. However, the reactive power is not shared accurately, through V/Q control loop and according to the droop gains, as the voltage is a local variable. Furthermore, considering the small scale of DG units, reactive power sharing should be implemented instantaneously to prevent DG units from overcurrent or even blackout of the MG. This paper deals with reactive power sharing issue in droop control-based MGs as well as stability and dynamic performance concerns of V/Q control loop. A servo control system is designed to control power converters in MGs, by which droop-based VSIs are converted to servo VSIs (S-VSIs). A novel decentralized method is proposed to obtain the reactive power set-points of S-VSIs according to their droop coefficients, and fuzzy particle swarm optimization method is used to optimize the S-VSI's parameters, so that, in addition to securing stability of the V/Q loop, the desired (fast) response in reference tracking is achieved. The simulation results show that the proposed strategy is effective and its performance is not affected by delay or interruption of the existing low bandwidth communication link.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Short-Term Spatio-Temporal Forecasting of Photovoltaic Power Production
    • Authors: Xwégnon Ghislain Agoua;Robin Girard;George Kariniotakis;
      Pages: 538 - 546
      Abstract: In recent years, the penetration of photovoltaic (PV) generation in the energy mix of several countries has significantly increased thanks to policies favoring development of renewables and also to the significant cost reduction of this specific technology. The PV power production process is characterized by significant variability, as it depends on meteorological conditions, which brings new challenges to power system operators. To address these challenges, it is important to be able to observe and anticipate production levels. Accurate forecasting of the power output of PV plants is recognized today as a prerequisite for large-scale PV penetration on the grid. In this paper, we propose a statistical method to address the problem of stationarity of PV production data, and develop a model to forecast PV plant power output in the very short term (0-6 h). The proposed model uses distributed power plants as sensors and exploits their spatio-temporal dependencies to improve forecasts. The computational requirements of the method are low, making it appropriate for large-scale application and easy to use when online updating of the production data is possible. The improvement of the normalized root mean square error (nRMSE) can reach 20% or more in comparison with state-of-the-art forecasting techniques.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Application of Stochastic Dual Dynamic Programming to the Real-Time
           Dispatch of Storage Under Renewable Supply Uncertainty
    • Authors: Anthony Papavasiliou;Yuting Mou;Léopold Cambier;Damien Scieur;
      Pages: 547 - 558
      Abstract: This paper presents a multistage stochastic programming formulation of a transmission-constrained economic dispatch subject to multiarea renewable production uncertainty, with a focus on optimizing the dispatch of storage in real-time operations. This problem is resolved using stochastic dual dynamic programming. The applicability of the proposed approach is demonstrated on a realistic case study of the German power system calibrated against the solar and wind power integration levels of 2013-2014, with a 24-h horizon and 15-min time step. The value of the stochastic solution relative to the cost of a deterministic policy amounts to 1.1%, while the value of perfect foresight relative to the cost of the stochastic programming policy amounts to 0.8%. The relative performance of various alternative real-time dispatch policies is analyzed, and the sensitivity of the results is explored.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Robust Design of Microgrids With Reconfigurable Topology Under Severe
           Uncertainty
    • Authors: Farhad Samadi Gazijahani;Javad Salehi;
      Pages: 559 - 569
      Abstract: The presence of uncertain parameters in design of microgrids (MG) adds significant challenges for MGs planner when it comes to making decisions. To address the uncertainties in the technical and pecuniary information especially in the case of lack of full information on the nature of uncertainty, this paper proposes a novel robust optimization approach for optimum design of MGs considering reconfigurable topology. The proposed approach investigates the economic and reliable structure for MGs deployment and optimal planning of distributed energy resources with section switch and tie switch (TSW) allocation to determine MGs boundaries and topologies. The optimal TSW allocation is implemented in order to change the configuration of distribution network to increase robustness of MGs versus uncertainty. The profit-based objective function is converted into robust framework and, subsequently, has been transformed into single level model by duality gap theory. Finally, grey wolf optimization algorithm has been carried out to solve the proposed model. The appraisement of the proposed model is accomplished by applying it on the IEEE 30-bus distribution system and results of case study demonstrate the effectiveness of the proposed method.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Adaptive Sensorless SM-DPC of DFIG-Based WECS Under Disturbed Grid: Study
           and Experimental Results
    • Authors: Abdelhak Djoudi;Seddik Bacha;Hachemi Chekireb;Hossein Iman-Eini;Cédric Boudinet;
      Pages: 570 - 581
      Abstract: This paper focuses on the enhanced control and improved fault-ride-through capability of a doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) under disturbed grid conditions. An adaptive sliding-mode control of stator powers, with sensorless rotor current and constant switching frequency, is introduced. The proposed control method is derived directly from the nonlinear DFIG state model, and the control law is computed based on nominal stator flux. Therefore, the flux estimation or measure, which is cumbersome in some methods, is no longer required. Furthermore, an adaptive term is added to sliding-mode control in order to attenuate the chattering effect. The proposed control law is validated via simulations in the case of 1.5 MW DFIG-based WECS, and experimental results on a 7.5 kW hardware prototype. The control system robustness and performance is assessed in the presence of modeling errors, parameter variations, and grid side disturbances, such as voltage dip, swell, imbalance, distortion, and flicker (according to IEEE Standard 1159).
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • A Bilevel Model for Participation of a Storage System in Energy and
           Reserve Markets
    • Authors: Ehsan Nasrolahpour;Jalal Kazempour;Hamidreza Zareipour;William D. Rosehart;
      Pages: 582 - 598
      Abstract: We develop a decision-making tool based on a bilevel complementarity model for a merchant price-maker energy storage system to determine the most beneficial trading actions in pool-based markets, including day-ahead (as joint energy and reserve markets) and balancing settlements. The uncertainty of net load deviation in real-time is incorporated into the model using a set of scenarios generated from the available forecast in the day-ahead. The objective of this energy storage system is to maximize its expected profit. The day-ahead products of energy storage system include energy as well as reserve commitment (as one of the ancillary services), whereas its balancing product is the energy deployed from the committed reserve. The proposed model captures the interactions of different markets and their impacts on the functioning of the storage system. It also provides an insight for storage system into clearing process of multiple markets and enables such a facility to possibly affect the outcomes of those markets to its own benefit through strategic price and quantity offers. The validity of the proposed approach is evaluated using a numerical study.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • A Droop Frequency Control for Maintaining Different Frequency Qualities in
           a Stand-Alone Multimicrogrid System
    • Authors: Thai-Thanh Nguyen;Hyeong-Jun Yoo;Hak-Man Kim;
      Pages: 599 - 609
      Abstract: Multiple microgrid (MG) systems can exist in a wide geographical area. They can interconnect and operate on different frequency qualities to enhance the penetration of renewable energy resources. To operate multiple MGs on different frequency qualities, a framework of the stand-alone multimicrogrid (MMG) system is proposed in this study. In the proposed MMG system, each MG connects to the common dc line through an ac/dc interlinking converter. A droop frequency control is proposed for the interlinking converter to improve frequency control performance and achieve autonomous power sharing. The sensitivity analysis with respect to the proposed control is performed to evaluate the stability of the converter system. The proposed droop frequency controller is evaluated in the MMG system with three MGs. The feasibility of the proposed controller is verified by the hardware-in-the-loop simulation using OPAL-RT technologies. The droop frequency controller is executed in digital signal processor TMS-320F-28335 while the proposed MMG system is modeled in a real-time simulator (OP5600). A comparison study on the proposed droop frequency control and conventional P/f control is presented. By using the proposed frequency control, the energy reserves in the adjacent microgrids can be shared effectively to achieve better performance of frequency regulation in the stand-alone MMG system.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • A Practical Equivalent Method for DFIG Wind Farms
    • Authors: Weixing Li;Pupu Chao;Xiaodong Liang;Jin Ma;Dianguo Xu;Xiaoming Jin;
      Pages: 610 - 620
      Abstract: With increasing penetration of wind power, it is recognized that manufacturer-specific models of wind turbines are not appropriate for power system studies, and the equivalent model of wind farms required by dynamic modeling poses a complicated technical challenge. In this paper, a practical equivalent method for wind farms with doubly fed induction generator (DFIG) wind turbines is proposed. Three critical steps are involved in this method. Step 1, modeling of a wind turbine, the model incorporating the complete fault ride through process is constructed and validated for an operational DFIG wind turbine. Step 2, clustering of wind turbines, a practical four-machine equivalent method is proposed. Initially, dynamic responses of active power of a DFIG wind turbine operating at various wind speeds are investigated to obtain three clusters of wind turbines, then four clusters are further determined by improving equivalency error at some typical wind speed scenarios. Step 3, an analytical method is proposed to determine the equivalent collector network parameters for each of the four equivalent machines. The proposed method is validated by comparing with the single-machine representation and the detailed wind farm model. Simulation results show that the proposed method has good performance for different fault durations, voltage dips, and changing wind scenarios.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Impact of Distributed Photovoltaic Systems on Zone Substation Peak Demand
    • Authors: Navid Haghdadi;Anna Bruce;Iain MacGill;Robert Passey;
      Pages: 621 - 629
      Abstract: Australia has likely the world's highest residential photovoltaic (PV) system penetration. In this paper, the impact of distributed PV on peak demand at different distribution network zone substations (ZSs) is assessed by upscaling 15 min PV generation data from 270 distributed PV systems across Sydney, Australia, and comparing it with load data from 138 ZS serving the Sydney region. Gross load (load had there been no PV) was estimated, allowing the impact of current and higher PV penetrations on the value and time of peak at the different ZSs to be assessed. A probabilistic assessment of the impact of PV on ZSs is conducted, based on the availability of PV during the peak demand periods. To better understand the impact of PV on peak demand, K-means clustering is used to group ZSs based on PV generation during peak periods as the clustering features. Mapping of PV availability across percentage of peak times for all ZSs highlights the interannual variability of peak reductions and the potential impact of short-term load shifting. The impact of different penetration levels of distributed PV on the peak demand of the entire distribution network is also assessed by aggregating the ZS loads.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • A Modified Active Power Control Scheme for Enhanced Operation of
           PMSG-Based WGs
    • Authors: Vijayapriya R.;Raja P.;Selvan M. P.;
      Pages: 630 - 638
      Abstract: This paper emphasizes the development of a simplified active power control scheme for enhanced operation of grid integrated permanent magnet synchronous generator based wind-driven generators (WGs). An active power reference generation scheme is proposed for the machine side converter (MSC) to inject active power into the grid even under grid disturbances, without violating system components rating. In this scheme, the controller employed for MSC adjusts the active power captured proportionate to the drop in the grid voltage upon considering wind speed and rotor speed. Furthermore, unlike dual vector control scheme, the grid side converter controller is implemented in a positive synchronous frame with the proposed current oscillation cancellation scheme to suppress the oscillations in dc-link voltage, active and reactive power of the grid and to obtain symmetrical sinusoidal grid current. Extensive analytical simulation has been carried out in PSCAD/ EMTDC to validate the superiority of proposed control scheme over the conventional schemes when WG is subjected to various grid disturbances. The reduced percentage of oscillation in the system parameters such as dc-link voltage and grid active power confirms the efficacy of the proposed method when compared with the conventional control techniques.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Optimized Dispatch of Energy Storage Systems in Unbalanced Distribution
           Networks
    • Authors: Jeremy Donald Watson;Neville R. Watson;Ioannis Lestas;
      Pages: 639 - 650
      Abstract: This paper presents a method to achieve optimal active and reactive power contributions from each energy storage system in an unbalanced distribution network to minimize power loss, while ensuring network current and voltage constraints are satisfied. By modeling loads as either constant current or constant impedance, the ac optimal power flow is transformed into a noniterative convex optimization problem. The application of capacity constraints, voltage constraints, and energy storage constraints in an unbalanced three-phase four-wire system is considered, addressing specific issues pertaining to unbalanced networks such as voltage unbalance and neutral voltage displacement. The proposed method is then used to demonstrate optimized dispatch of energy storage systems in a suitable four-wire unbalanced distribution test network. The contribution of losses in the neutral wire to the total losses is also determined for a test system under a range of operating conditions and various neutral earthing systems, highlighting the importance of considering this in a typical unbalanced distribution network.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Robust Capacity Assessment of Distributed Generation in Unbalanced
           Distribution Networks Incorporating ANM Techniques
    • Authors: Xin Chen;Wenchuan Wu;Boming Zhang;
      Pages: 651 - 663
      Abstract: To settle a large-scale integration of renewable distributed generations (DGs), it requires to assess the maximal DG hosting capacity of active distribution networks (ADNs). For fully exploiting the ability of ADNs to accommodate DG, this paper proposes a robust comprehensive DG capacity assessment method considering three-phase power flow modelling and active network management (ANM) techniques. The two-stage adjustable robust optimization is employed to tackle the uncertainties of load demands and DG outputs. With our method, system planners can obtain the maximum penetration level of DGs with their optimal sizing and sitting decisions. Meanwhile, the robust optimal ANM schemes can be generated for each operation time period, including network reconfiguration, on-load-tap-changers regulation, and reactive power compensation. In addition, a three-step optimization algorithm is proposed to enhance the accuracy of DG capacity assessment results. The optimality and robustness of our method are validated via numerical tests on an unbalanced IEEE 33-bus distribution system.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Battery Energy Storage System Control for Intermittency Smoothing Using an
           Optimized Two-Stage Filter
    • Authors: Hamidreza Nazaripouya;Chi-Cheng Chu;Hemanshu Roy Pota;Rajit Gadh;
      Pages: 664 - 675
      Abstract: A new method for the control of a battery energy storage system and its implementation on a 25 kW solar system to compensate solar power intermittency and improve distribution grid power quality is presented in this paper. The novelty of the proposed method is to provide a systematic way to optimize the size of the battery capacity for the desired level of solar power smoothing. This goal is achieved by designing a two-stage filter solution. The first stage is a fast response digital finite impulse response (FIR) filter that makes a trade-off between smoothing of the solar output and battery capacity. This paper proposes an optimal design of a minimum-length, low-group-delay FIR filter by employing convex optimization, discrete signal processing, and polynomial stabilization techniques. The new strategy proposed in this paper formulates the design of a length-N low-group-delay FIR filter as a convex second-order cone programming, which guarantees that all the filter zeros are inside the unit circle (minimum-phase). A quasi-convex optimization problem is formulated to minimize the length of the low-group-delay FIR filter. The second-stage filter is designed to level the battery charging load. The effectiveness and performance of the proposed approach is demonstrated by simulation results and also over a real-case implementation.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Frequency Support From Wind Turbine Generators With a Time-Variable Droop
           Characteristic
    • Authors: Mehdi Garmroodi;Gregor Verbič;David J. Hill;
      Pages: 676 - 684
      Abstract: The changing inertia profile caused by the increased penetration of inertialess renewable energy sources has raised concerns about power system frequency control. The kinetic energy of the turbines in wind turbine generators (WTGs) can be utilized to support power system frequency during contingencies. In this paper, we investigate the frequency support capability of WTGs operating at the maximum power point (MPP). The requirements to prevent secondary frequency dips, provoked from switching between normal operating mode and the frequency support mode, are formulated. A time-variable droop characteristic is proposed for frequency support from WTGs, which is quite effective in preventing large frequency excursions and facilitates smooth recovery of the kinetic energy of WTGs. The performance of the proposed method is examined in different operating conditions of WTGs in a single bus model of power systems, as well as a regional 14-generator model of the Australian National Electricity Market. The results show that with the time-variable droop characteristic, the frequency nadir following a contingency can be largely improved and simultaneously, the WTGs can smoothly regain their kinetic energy and continue operating at the MPP.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Gas-Constrained Secure Reserve Allocation With Large Renewable Penetration
    • Authors: Andrea Antenucci;Giovanni Sansavini;
      Pages: 685 - 694
      Abstract: Gas-fired generation provides flexibility to the power system for peak-load shaving and reserve allocation. Large penetration of renewables strengthens the gas-electric coupling. Consequently, constraints to the operations of the high-pressure gas transmission system may endanger the security of power supply. To address this issue, we assess the impact of gas constraints on the day-ahead electric power and reserve scheduling. Furthermore, we investigate the effect of unforeseen, large negative ramps of wind power generation on the gas network operations. The day-ahead scheduling of electric generator dispatch and reserves is determined via a stochastic, N-1 secure optimization. Minimum-pressure constraints update the scheduling of electric generators and reserves. The simplified energy infrastructure of Great Britain in the 2030 Gone Green scenario is investigated for diverse gas load and wind availability conditions. Results show that large gas demands decrease linepack and cause gas-fired units to shut down due to minimum pressure violations. In scarce-wind conditions, gas network limitations largely affect reserve scheduling and nonelectric gas curtailments are needed to comply with pressure safety margins. Conversely, reserve planning including gas constraints prevents pressure violations caused by unexpected wind fluctuations. These results support operators and regulators by providing a technoeconomical evaluation of the gas-electric interdependencies.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • An Offer Strategy for Wind Power Producers That Considers the Correlation
           Between Wind Power and Real-Time Electricity Prices
    • Authors: Hunyoung Shin;Duehee Lee;Ross Baldick;
      Pages: 695 - 706
      Abstract: This paper provides a comprehensive analysis of how the correlation between wind power and electricity prices affects the offer strategies of wind power producers (WPPs). In a market that has a high penetration of wind energy, the correlation can be noticeable and thus should be considered by the WPPs when building offer strategies. First, this paper aims to build an advanced offer curve that considers the joint information of wind power and real-time (RT) prices. Then, we explore the sensitivity of the expected profit, value at risk (VaR), and conditional value at risk (CVaR) for the advanced offer curves to the probabilistic parameters of wind power and RT prices. We find that an offer curve which reflects this correlation generally results in a small improvement in expected profit, but a meaningful reduction in risks. The benefits of the advanced offer curves increase as the correlation becomes more negative or the variances of wind power and prices increase.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Bilevel Arbitrage Potential Evaluation for Grid-Scale Energy Storage
           Considering Wind Power and LMP Smoothing Effect
    • Authors: Hantao Cui;Fangxing Li;Xin Fang;Hao Chen;Honggang Wang;
      Pages: 707 - 718
      Abstract: This paper deals with extended-term energy storage (ES) arbitrage problems to maximize the annual revenue in deregulated power systems with high-penetration wind power. The conventional ES arbitrage model takes the locational marginal prices (LMP) as an input and is unable to account for the impacts of ES operations on system LMPs. This paper proposes a bilevel ES arbitrage model, where the upper level maximizes the ES arbitrage revenue and the lower level simulates the market clearing process considering wind power and ES. The bilevel model is formulated as a mathematical program with equilibrium constraints) and then recast into a mixed-integer linear programming using strong duality theory. Wind power fluctuations are characterized by the GARCH forecast model and the forecast error is modeled by forecast-bin-based Beta distributions. Case studies are performed on a modified PJM 5-bus system and an IEEE 118-bus system with a weekly time horizon over an annual term to show the validity of the proposed bilevel model. The results from the conventional model and the bilevel model are compared under different ES power and energy ratings, and also various load and wind penetration levels.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Insights on the Provision of Frequency Support by Wind Power and the
           Impact on Energy Systems
    • Authors: Ayman Bakry Taha Attya;Jose Luis Dominguez-García;
      Pages: 719 - 728
      Abstract: This paper implements and compares between the key concepts to enable wind power short-term frequency support from electrical and mechanical loads perspectives. Pitch de-loading, kinetic energy extraction, and wind turbine (WTG) over-speeding are investigated, where each concept is integrated as a supplementary controller to the conventional controls of WTG. Different patterns of wind speed are examined, step-change and real intermittent of high resolution. The examined aggregated synchronous area has a relatively high wind penetration with frequency support. The overall dynamic inertia of the system is assessed to analyze the impact of the integrated support methods and their key parameters. The coordination between synchronous areas and wind farms, which are interconnected through a multiterminal high-voltage direct-current network (MT-HVDC) is examined. A novel definition of the virtual inertia of MT-HVDC grid is proposed. Results show that pitch de-loading secures support reserve most of the time, and kinetic energy extraction provides sustainable support for a short interval, while accelerative de-loading could reach a compromise. The three methods are adaptable with the MT-HVDC holistic frequency support controller, with a slight advantage of kinetic energy extraction over the virtual inertia of the MT-HVDC. MATLAB/Simulink is the simulation environment.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • A Methodology for Optimal Distributed Storage Planning in Smart
           Distribution Grids
    • Authors: Mohammad Ghasemi Damavandi;José R. Martí;Vikram Krishnamurthy;
      Pages: 729 - 740
      Abstract: This paper proposes a methodology for optimal planning of distributed storage systems (DSS) in smart grids with high penetration of renewable sources. The DSS can provide distribution systems with various benefits, including arbitrage gain, reduction in the system losses, system resilience enhancement, reduction in nondispatchable energy curtailment, and peak load shaving. In particular, by alleviating the peak load, the system upgrade time can be deferred to future years, resulting in noticeable financial gains for the system operator. In this paper, the problem of DSS planning for optimizing the discounted economic gain of the system operator is formulated and solved as a mixed-integer convex program. Various economic gains are taken into account and the stochasticity of the loads and renewable generations is accounted for by evaluating the total expected gain. Numerical results for DSS planning on a 69-node, 11-kV smart grid and using real data of smart meters and renewable energy sources are presented and discussed.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • A Day-Ahead Forecasting Model for Probabilistic EV Charging Loads at
           Business Premises
    • Authors: Md Shariful Islam;Nadarajah Mithulananthan;Duong Quoc Hung;
      Pages: 741 - 753
      Abstract: Focusing on every individual electric vehicle (EV) while optimally charging a significant number of EV units at the workplace is normally computationally burdensome. Such charging optimization requires not only a long runtime but also a large CPU memory due to numerous decision variables involved. This paper develops a new combined state of charge (SOC) based methodology to calculate day-ahead combined probabilistic charging loads for a large number of EV units. Here, several models are proposed to estimate different combined statistical parameters based on historical data. The proposed methodology determines the transition of the combined SOC distribution of EV units from one timeslot to the next using these estimated parameters. Various strategies of SOC-based charging (e.g., unfair and fair modes) are investigated to control EV loads. Numerical results show that the proposed SOC-based charging can reduce the number of decision variables significantly, and require less computational time and memory accordingly.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Real-Time Estimation of Areal Photovoltaic Power Using Weather and Power
           Flow Data
    • Authors: Kyohhei Kamono;Yuzuru Ueda;
      Pages: 754 - 762
      Abstract: To stably operate the power grid under a mass introduction of photovoltaic systems, a method to estimate the areal photovoltaic power in real time is necessary. The estimation method proposed in this paper achieves high accuracy by separately estimating the high- and low-frequency components of photovoltaic power. The high-frequency component is estimated using power flow at the distribution substation, whereas the low-frequency component is estimated using solar irradiance, ambient temperature, power flow, and if available 30-min integrated values of the electric load measured by smart meters. To evaluate the proposed method, simulations using measured data were performed. These were performed under four scenarios depending on the acceptance of a 15-min delay and the availability of smart meter data. In the best-case scenario, where 15-min delays to estimate the areal photovoltaic power is accepted and smart meter data are available, the estimation was performed with yearly root-mean-square error of approximately 2.2% of the total system capacity. Even in the worst-case scenario, where 15-min delays were unaccepted and smart meters not installed, the estimation was performed with yearly root-mean-square error of approximately 3.7% of the system capacity.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Scalable Coordinated Control of Energy Storage Systems for Enhancing Power
           System Angle Stability
    • Authors: Mohammadali Rostami;Saeed Lotfifard;
      Pages: 763 - 770
      Abstract: In this paper, a scalable wide area control scheme using distributed model predictive control is proposed to enhance the angle stability of power systems following large disturbances. In this regard, dynamic model of the local subsystems in the multiarea power system is developed for the model predictive controller and each subsystem is controlled by the associated controller. The controller of each subsystem exchanges minimum information with the controllers of the neighboring subsystems to reach the final result. The proposed controller works based on optimality condition decomposition to coordinate the subsystems. In the proposed wide area control system, the available actuators are mechanical power and field voltage controller of a synchronous generator, and energy storage systems (ESS), which are able to provide synchronizing power support. The performance of the proposed transient stability controller is studied in the New England 68-bus test system. The simulation results demonstrate the effectiveness of the proposed method to improve the angle stability of power systems subsequent to severe disturbances in the system.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • A Comprehensive Algorithm for Estimating Lithium-Ion Battery Parameters
           From Measurements
    • Authors: Dominik Dvorak;Thomas Bäuml;Alexandra Holzinger;Hartmut Popp;
      Pages: 771 - 779
      Abstract: The use of equivalent circuit models for simulating the operating behavior of lithium-ion batteries is well established in the automotive and the renewable energy sector. However, finding the correct parameter set for these models is still a challenging task. This manuscript proposes a comprehensive methodology for estimating the required, temperature dependent simulation parameters from battery measurements. Based on a specific load current and prior system knowledge, an algorithm first analyses the correlation between current steps and the measured terminal voltage. Second, a combination of particle swarm optimization and Gauss-Newton algorithm fits the initially estimated parameters from the first algorithm to the measurement data. Finally, the dependency of each simulation parameter on both the state of charge and the battery temperature is determined. As this contribution aims at modeling reversible effects of lithium-ion batteries, ageing effects are neglected. The validation against measurement data proves that the generated parameter set enables the user to accurately reproduce and investigate the operating behavior of the chosen battery. Applied to a lithium-iron-phosphate cell, the comparison between measurements and simulations in standardized real-life automotive driving cycles (Artemis, FTP75 and WLTC) shows a terminal voltage error of less than 1.09% within the typical operational window between state of charge 0.15 and 0.95.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Coordinated Supplementary Damping Control of DFIG and PSS to Suppress
           Inter-Area Oscillations With Optimally Controlled Plant Dynamics
    • Authors: Chen Zhang;Deping Ke;Yuanzhang Sun;C. Y. Chung;Jian Xu;Feifan Shen;
      Pages: 780 - 791
      Abstract: This paper proposes a design method to coordinate dual-channel supplementary damping controllers (SDCs) of doubly-fed induction generators (DFIGs) and power system stabilizers (PSSs) for suppression of inter-area power oscillations. A dynamic performance index is introduced to measure the dynamics of the conventional synchronous generator and DFIG during the damping control process. Hence, the proposed method designing the PSS and SDC is formulated as an optimization problem with the objective function being the sum of weighted performance indexes and the constraints indicating the requirements on the damping of the inter-area modes. Solving the optimization problem can obtain the optimal SDC and PSS, which can meet the required damping results as well as optimize dynamics of the controlled plants. Moreover, by adjusting weights in the objective function, the damping control burden can be flexibly and feasibly allocated between active and reactive power channels of DFIGs or among the damping controllers. Simulations with the modified New England and New York interconnected system prove that the proposed optimization based tuning method can not only robustly coordinate the PSS and SDC to effectively damp inter-area oscillations but also improve the dynamics of controlled plants during the damping control process over different operating conditions.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • DFIG Wind Generators Fault Diagnosis Considering Parameter and Measurement
           Uncertainties
    • Authors: Aslan Mojallal;Saeed Lotfifard;
      Pages: 792 - 804
      Abstract: Accurate and fast fault detection and isolation/identification (FDI) in wind power generators minimizes the downtime of the units as further damages can be prevented. In this paper, a robust FDI method for doubly fed induction generator (DFIG) based wind generators based on bond-graph (BG) theory is proposed. The comprehensive model of BG model of DFIG-based wind generators is developed that includes electrical, mechanical, and hydraulic subsystems. To represent the parameter uncertainties in the BG model, linear fractional transformation is utilized, in which the uncertain part of the BG model is separated from the nominal part of the model. Based on the nominal part of the BG model, analytical redundancy relationships are derived that are used for FDI. The uncertain part of the BG model is also used to derive the thresholds that are used for distinguishing faulty cases from nonfaulty cases in the presence of uncertainty. Results obtained from the case study, demonstrate that the proposed method is capable of detecting and pinpointing faults in different components, quickly and accurately.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Application of Information Gap Decision Theory to the Design of Robust
           Wide-Area Power System Stabilizers Considering Uncertainties of Wind Power
           
    • Authors: Deping Ke;Feifan Shen;C. Y. Chung;Chen Zhang;Jian Xu;Yuanzhang Sun;
      Pages: 805 - 817
      Abstract: This paper proposes the application of information gap decision theory (IGDT) to the design of robust wide-area power system stabilizers (WPSSs) with consideration of wind farm (WF) power outputs variations and transmission line outages. According to IGDT, an optimization problem is constructed to tune WPSS parameters. Then, the derived optimal WPSSs can achieve explicit and favorable robustness to ensure the required damping control effects on the interarea oscillations over a maximum variation range of WF steady-state power outputs in normal and emergent operating conditions. Moreover, with the intent of using the excellent global searching capability of particle swarm optimization (PSO), a customized PSO algorithm is proposed to efficiently solve the resulting highly nonlinear programming problem. Finally, simulations are carried out on a modified New England (10-machine 39-bus) system to validate the efficiency of the IGDT-based design method. The derived WPSSs exhibit expected robustness with respect to the wind power variations and transmission line outages.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Bayesian and Robust Nash Equilibria in Hydrodominated Systems Under
           Uncertainty
    • Authors: Ekaterina Moiseeva;Mohammad Reza Hesamzadeh;
      Pages: 818 - 830
      Abstract: In this paper, we model strategic interaction of multiple producers in hydrodominated power systems under uncertainty as an equilibrium problem with equilibrium constraints (EPEC), reformulated as a stochastic mixed-integer linear program with disjunctive constraints. We model strategic hydropower producers who can affect the market price by submitting strategic bids in quantity, price, and ramp rate. The bids are submitted to the system operator who minimizes the dispatch cost. We take into account the hydrospecific constraints and uncertainty in the system. Solving the problem results in finding Nash equilibria. We discuss two types of Nash equilibria under uncertainty: Bayesian and robust Nash equilibria. Large EPEC instances can be solved using a decomposition method-Modified Benders Decomposition Approach. This method eliminates the problem of tuning the disjunctive parameter and reduces the memory requirements, resulting in improved computation time.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Day-Ahead Hourly Forecasting of Power Generation From Photovoltaic Plants
    • Authors: Lorenzo Gigoni;Alessandro Betti;Emanuele Crisostomi;Alessandro Franco;Mauro Tucci;Fabrizio Bizzarri;Debora Mucci;
      Pages: 831 - 842
      Abstract: The ability to accurately forecast power generation from renewable sources is nowadays recognized as a fundamental skill to improve the operation of power systems. Despite the general interest of the power community in this topic, it is not always simple to compare different forecasting methodologies, and infer the impact of single components in providing accurate predictions. In this paper, we extensively compare simple forecasting methodologies with more sophisticated ones over 32 photovoltaic (PV) plants of different sizes and technology over a whole year. Also, we try to evaluate the impact of weather conditions and weather forecasts on the prediction of PV power generation.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Shipboard Microgrids: A Novel Approach to Load Frequency Control
    • Authors: Mohammad-Hassan Khooban;Tomislav Dragicevic;Frede Blaabjerg;Marko Delimar;
      Pages: 843 - 852
      Abstract: Due to the fast development of renewable energy systems and the severe limitations enforced by the marine pollution protocol, the utilizing of wind turbines (WTs), solar generation, sea wave energy (SWE), and energy storage systems (ESS) in marine vessel power systems have been attracting a lot of attention. Hence, a marine vessel power system with photovoltaic, WT, SWE, and ESS can be considered as a specific mobile islanded microgrid. Consequently, the main target of this paper is to design a new optimal fractional order fuzzy PD+I load frequency controller (LFC) for islanded microgrids in a ship power system. Since the performance of the controller depends on its parameters, the optimization of these coefficients can play a significant role in improving the output performance of the LFC control. Accordingly, a modified black hole optimization algorithm is utilized for the adaptive tuning of the coefficients of noninteger fuzzy PD+I controller. The performance of the shipboard microgrid is evaluated by utilizing real-world wind power fluctuation and solar radiation data. Finally, the extensive studies and hardware-in-the-loop simulations are applied to prove that the proposed controller can track the reference frequency with lower deviation as well as it is more robust in comparison with the prior-art controllers utilized in the case studies.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Load Frequency Control in Microgrids Based on a Stochastic Noninteger
           Controller
    • Authors: Mohammad-Hassan Khooban;Taher Niknam;Mokhtar Shasadeghi;Tomislav Dragicevic;Frede Blaabjerg;
      Pages: 853 - 861
      Abstract: In this paper, an adaptive multiobjective fractional-order fuzzy proportional-integral-derivative controller is proposed for the load frequency control (LFC) of islanded microgrids (MGs), while benefiting from the assets of electric vehicles (EVs) in this respect. Although the use of battery energy storage systems (BESS) can solve the unbalance effects between the load and supply of an isolated MG, their high cost and tendency toward degradation are restrictive factors, which call for the use of alternative power balancing options. In recent years, the concept of utilizing the BESSs of EVs, also known as vehicle-to-grid (V2G) concept, for frequency support of MGs has attracted a lot of attention. In order to allow the V2G controller operate optimally under a wide range of operation conditions caused by the intermittent behavior of renewable energy resources, a new multiobjective fractional-order control strategy for the EVs in V2G scenarios is proposed in this paper. Moreover, since the performance of the controller depends on its parameters, optimization of these parameters can play a significant role in promoting the output performance of the LFC control; hence, a modified black hole optimization algorithm is utilized for the adaptive tuning of the noninteger fuzzy PID controller coefficients. The performance of the proposed LFC is evaluated by using real world wind and solar radiation data. Finally, the extensive studies and hardware-in-the-loop simulations are presented to prove that the proposed controller tracks frequency with lower deviation and fluctuation and is more robust in comparison with the prior-art controllers used in all the case studies.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Optimized Power Dispatch in Wind Farms for Power Maximizing Considering
           Fatigue Loads
    • Authors: Baohua Zhang;Mohsen Soltani;Weihao Hu;Peng Hou;Qi Huang;Zhe Chen;
      Pages: 862 - 871
      Abstract: Wake effects in a wind farm (WF) include the wind velocity deficit and the added turbulence. The wind velocity deficit may bring significant loss of the wind power and the added turbulence may cause extra fatigue load on the wind turbines (WTs). Inclusion of the wake effects in the wind farm control design can increase the total captured power by derating the upwind WTs. However, this may increase the turbulence and cause more fatigue load on the downwind WTs. This paper proposes an optimized active power dispatch strategy for WFs to maximize the total captured power while maintaining the fatigue load of the shafts and the towers within a certain range from the values using traditional strategy, which adopts maximum power point tracking (MPPT) control for each WT. A WT derating control strategy is included in the WT controller and the fatigue load for the tower and shaft is evaluated offline at a series of turbulence intensity, mean wind speed and active power reference to form a lookup table, which is used for the WF control. The proposed strategy is compared with WT MPPT control strategy and WF MPPT control strategy. The simulation results show the effectiveness of the proposed strategy.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Multistage Multiresolution Robust Unit Commitment With Nondeterministic
           Flexible Ramp Considering Load and Wind Variabilities
    • Authors: Mohammad Iman Alizadeh;Mohsen Parsa Moghaddam;Nima Amjady;
      Pages: 872 - 883
      Abstract: This paper investigates the impacts of integrating nondeterministic flexible ramp reserves in a multistage multiresolution day-ahead robust unit commitment to cope with variability of renewable energy sources. While the common literature considers deterministic forms of flexible ramp reserves, the proposed affinely adjustable robust UC model considers explicit endogenous up and down subhourly ramp reserve deployment to effectively allocate flexible ramp capacities. In addition, unlike the conventional noncausal two-stage robust unit commitment models that immunize solutions against worst economic scenario with the dependency of decisions on the future information of uncertainty, the current nonconservative multistage model optimizes hourly commitment and dispatch scheduling for the base-case scenario, while ensuring that the specified subhourly causal ramp reserves can be adaptively adjusted. Moreover, dimensionality limitations of the conventional duality-based affinely adjustable robust optimizations are resolved. The effectiveness of the proposed model compared with conventional robust unit commitment frameworks is extensively illustrated on the IEEE 24-bus reliability test system and the IEEE 118-bus test system.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Robust Joint Expansion Planning of Electrical Distribution Systems and EV
           Charging Stations
    • Authors: Nataly Bañol Arias;Alejandra Tabares;John F. Franco;Marina Lavorato;Rubén Romero;
      Pages: 884 - 894
      Abstract: Electrical distribution systems (EDSs) should be prepared to cope with demand growth in order to provide a quality service. The future increase in electric vehicles (EVs) represents a challenge for the planning of the EDS due to the corresponding increase in the load. Therefore, methods to support the planning of the EDS, considering the uncertainties of conventional loads and EV demand, should be developed. This paper proposes a mixed-integer linear programming (MILP) model to solve the robust multistage joint expansion planning of EDSs and the allocation of EV charging stations (EVCSs). Chance constraints are used in the proposed robust formulation to deal with load uncertainties, guaranteeing the fulfillment of the substation capacity within a specified confidence level. The expansion planning method considers the construction/reinforcement of substations, EVCSs, and circuits, as well as the allocation of distributed generation units and capacitor banks along the different stages in which the planning horizon is divided. The proposed MILP model guarantees optimality by applying classical optimization techniques. The effectiveness and robustness of the proposed method is verified via two distribution systems with 18 and 54 nodes. Additionally, Monte Carlo simulations are carried out, aiming to verify the compliance of the proposed chance constraint.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Framework of Maximum Power Extraction From Solar PV Panel Using Self
           Predictive Perturb and Observe Algorithm
    • Authors: Nishant Kumar;Ikhlaq Hussain;Bhim Singh;Bijaya Ketan Panigrahi;
      Pages: 895 - 903
      Abstract: This paper deals with a new version of perturb and observe tracking algorithm for maximum power extraction from the solar photovoltaic panel, which has self-predictive and decision taking ability. The working principle of self-predictive perturb and observe (SPP&O) algorithm is based on three consecutive operating points on the power-voltage characteristic. Out of three points, first two points very smartly detects the dynamic condition, as well as in normal condition, quickly searches the maximum power point (MPP) region. Moreover, by using a circular analogy, all points decide the optimal operating position for next iteration, which is responsible for quick MPP tracking as well as improved dynamic performance. Here, in every new iteration, the step-size is reduced by 90% from the previous step-size, which provides an oscillation-free steady-state performance. The effectiveness of the proposed technique is validated by MATLAB simulation as well as tested on hardware prototype. Moreover, comparison between SPP&O algorithm and state of art methods is made. Its satisfactory dynamic and steady-state behaviors with low algorithm complexity as well as the low computational burden of the SPP&O algorithm show the superiority over state of the art methods.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Flexible Interlinking and Coordinated Power Control of Multiple DC
           Microgrids Clusters
    • Authors: Xialin Li;Li Guo;Yunwei Li;Chao Hong;Ye Zhang;Zhen Guo;Di Huang;Chengshan Wang;
      Pages: 904 - 915
      Abstract: Multiple distributed dc microgrids (MGs) in a close vicinity can be connected to each other to form a dc MG cluster. Especially with isolated bidirectional dc-dc converters (IBDCs) as the active interconnected devices, flexible power control and electrical isolation among the dc MGs can be realized. A novel coordinated power control framework for such a cluster has been proposed in this paper, in which the dc MGs adopt the standard droop control, and a unified control is proposed for the IBDCs. In normal operation, autonomous flexible interlinking power control among the distributed dc MGs can be achieved through the unified control of IBDCs, making the demand of the power terminals to be proportionally shared among the slack terminals in the dc cluster. Furthermore, with the unified control, if one of the dc MGs loses dc voltage control capability due to the outage of its slack terminal, the interlinked IBDCs can transfer to dc MG support control mode automatically and seamlessly without control scheme switching and operation mode detection. In addition, when there is a dc bus fault in one of the subsystems, the interconnected IBDC can lockout its control signals and isolate the dc fault, to ensure stable operation of the rest of the dc MGs within the cluster. Finally, PSCAD/EMTDC based simulation verifications and experimental results obtained from a hardware prototype have been provided.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Optimal Operation of Emerging Flexible Resources Considering Sub-Hourly
           Flexible Ramp Product
    • Authors: Ehsan Heydarian-Forushani;Mohamad Esmail Hamedani Golshan;Miadreza Shafie-khah;Pierluigi Siano;
      Pages: 916 - 929
      Abstract: To deal with high variability of stochastic market operations and with the aim of assuring a feasible and economic operation under high renewable energy sources penetration, in this paper two applicable solutions are proposed: 1) the incorporation into the electricity market of emerging flexible resources, including demand response, bulk energy storages, and plug-in electric vehicle parking Lots considering their own specific characteristics; and 2) a new flexible ramp market in order to cope with sudden variations and guarantee the rampability of reserve capacity provided by a generation portfolio. On this basis, an integrated stochastic day-ahead market clearing model has been developed to solve the energy, reserve, and flexible ramp scheduling considering a real-time power balance problem, reflecting the 5 min.-by-5 min. renewable energy source and demand changes. Numerical tests are conducted on a modified IEEE RTS 24-bus and the obtained results validate the applicability of proposed model.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • A Control Strategy for Multiterminal DC Grids With Renewable Production
           and Storage Devices
    • Authors: Miguel Jiménez Carrizosa;Amir Arzandé;Fernando Dorado Navas;Gilney Damm;Jean-Claude Vannier;
      Pages: 930 - 939
      Abstract: This paper provides a solution for the control of multiterminal dc networks from the point of view of the network's transmission system operator, which includes local, primary, and secondary controllers. A new power flow technique is validated for this approach, which guarantees the stability and requires fewer calculations than the conventional techniques. This study also describes an optimal control strategy for intermittent (renewable) energy producers, where the controller periodically transmits information about its state to the system operator. Its main goal is to optimize economic profit for the producer. This last controller is implemented via model predictive control. The whole control strategy is validated in a scaled dc grid test-bench with four nodes. Real solar production (5 kW rated power), a storage system, as well as short-term weather and consumption forecasts are also included.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Optimal Day-Ahead Scheduling of Power-to-Gas Energy Storage and Gas Load
           Management in Wholesale Electricity and Gas Markets
    • Authors: Hadi Khani;Hany Essa Zidan Farag;
      Pages: 940 - 951
      Abstract: Power-to-gas (PtG) energy storage converts electricity to hydrogen or synthetic natural gas. The gas produced is stored and converted back to electricity at a later time; or it is directly used to supply a gas load and/or sell in the gas market. In the first case, due to double energy conversion in a relatively less efficient process, a large portion of the energy is wasted. The latter case is examined in this paper, where PtG storage is optimally scheduled to convert waste/inexpensive electricity to synthetic natural gas for some useful operations at appropriate time periods. To that end, a new model is proposed for optimal day-ahead scheduling of PtG storage and gas load management in electricity and gas markets to minimize the cost of gas consumption for the gas load. A gas demand forecasting algorithm is integrated into the scheduling model. Reserve provision is formulated as part of the optimization problem to optimally manage the gas load in case of an outage in the gas grid. The application of the proposed model to a test case is examined, and the results are studied.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Stochastic Model for Generation of High-Resolution Irradiance Data and
           Estimation of Power Output of Photovoltaic Plants
    • Authors: Cleber Onofre Inácio;Carmen Lucia Tancredo Borges;
      Pages: 952 - 960
      Abstract: This paper presents a method for the generation of synthetic time series of solar radiation with a one-minute time resolution using an automatic cloud classification procedure. Solar radiation data from ground-based measurements are used to determine the correlation between the irradiance and the prevailing cloud classes extracted from satellite images. A specific set of Markov chains for each cloud class is adjusted empirically and used for a stochastic simulation of clear sky index time series. The different models are then combined to convert the irradiance into power output time series of photovoltaic power plants of different sizes. Tests to determine the methodology's performance showed positive results in reproducing the statistical characteristics of observed time series data. Estimates of a selected set of metrics were obtained for several sites in Brazil and allowed the characterization of the solar resource for photovoltaic plants of various sizes and mounting methods considering the generation potential and short-term variability.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Cost-Benefit Analysis of V2G Implementation in Distribution Networks
           Considering PEVs Battery Degradation
    • Authors: Ali Ahmadian;Mahdi Sedghi;Behnam Mohammadi-ivatloo;Ali Elkamel;Masoud Aliakbar Golkar;Michael Fowler;
      Pages: 961 - 970
      Abstract: Charging of plug-in electric vehicles (PEVs), especially as market penetration increases, is an important challenge for today's power systems. This paper presents a stochastic methodology for smart charging of PEVs. All of the associated uncertainties are taken into account in the proposed methodology. Moreover, a comprehensive model for impact of charging/discharging strategies on the battery pack degradation in the vehicle has been included. The proposed approach is applied to a typical distribution network that contains wind-based distributed generation (DG) units. A cost-benefit analysis is carried out to extract the benefits of Vehicle to Grid (V2G) implementation in distribution network. The simulation results show that the V2G implementation without considering battery degradation is economical. However, when considering a battery degradation cost, V2G implementation without wind generation is not beneficial, while it is economical when considering wind DG. Moreover, the smart charging is economical in all conditions and also it reduces the battery degradation cost in comparison with uncoordinated charging.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Hierarchical Bayesian Model for Estimating Spatial-Temporal Photovoltaic
           Potential in Residential Areas
    • Authors: Joel Villavicencio Gastelu;Joel David Melo Trujillo;Antonio Padilha-Feltrin;
      Pages: 971 - 979
      Abstract: This paper presents a Bayesian hierarchical model to estimate the spatial-temporal photovoltaic potential in residential areas. The proposed model offers a probabilistic approach that uses technical criteria of planners and favorable socioeconomic conditions for installing photovoltaic systems. Thus, the inhabitants' distrust of the photovoltaic solar energy choice is modeled via random distributions. The results are a spatial database that allows the creation of thematic maps to visualize the spatial distribution of photovoltaic potential in cities' residential areas for each year of the planning horizon. The proposed methodology was applied to a medium-sized city in Brazil. Maps which came from the application show the subareas with higher photovoltaic potential, where a range of impacts could appear on the distribution networks. Therefore, the results can contribute to multiscenario planning and operation studies of low- and medium-voltage networks performed by utility companies.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Priority-Based Microgrid Energy Management in a Network Environment
    • Authors: Mohsen Rafiee Sandgani;Shahin Sirouspour;
      Pages: 980 - 990
      Abstract: The paper presents a method for energy storage dispatch and sharing of renewable energy resources in a network of grid-connected microgrids. The proposed scheme provides for local inter-microgrid and microgrid-to-grid power transactions, enabling them to collectively share their storage and renewable energy capacity in order to reduce their electricity cost. The storage dispatch commands and the share of local and grid power transactions for the individual microgrids are determined by solving a multi-objective optimization problem over a receding control horizon, using forecasts of the net power demands of the microgrids. This multi-objective optimization is formulated as a lexicographic program, to allow for preferential treatment of groups of microgrids based on pre-assigned priorities. The original optimization model is convex but nonlinear. A linear counterpart of the problem is derived that is suitable for online computation. Numerical simulations with real demand and renewable generation data demonstrate the effectiveness of the proposed strategy in reducing the electricity costs of the microgrids in accordance to their priority in the network.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
  • Demand Response and Renewable Energy Management Using Continuous-Time
           Optimization
    • Authors: Johann Leithon;Sumei Sun;Teng Joon Lim;
      Pages: 991 - 1000
      Abstract: Facilities with limited flexibility to schedule their power consumption, such as office buildings or commercial establishments, can be modeled as time-varying nondeferrable loads. In this paper, we propose a demand response strategy for a nondeferrable load facility with renewable energy harvesting and storage capabilities. We assume time-varying electricity prices, and devise a strategy to minimize the expected energy cost incurred by the facility over a finite planning horizon. Unlike existing works, we derive our results by using a generalized model for the energy storage device, which takes into account the nonlinear relationship between the discharging rate and the remaining charge. Moreover, we use continuous-time optimization to obtain explicit results, which are meant to reduce the computational complexity of existing strategies. Finally, we use simulations to show that the proposed strategy outperforms the state of the art, especially when the battery discharging model is strictly nonlinear.
      PubDate: April 2018
      Issue No: Vol. 9, No. 2 (2018)
       
 
 
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