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3C TIC     Open Access   (Followers: 1)
Actuators     Open Access   (Followers: 4)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 1)
Advances in Electrical Engineering     Open Access   (Followers: 18)
Advances in Microelectronic Engineering     Open Access   (Followers: 11)
Advances in Signal Processing     Open Access   (Followers: 11)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 23)
American Journal of Sensor Technology     Open Access   (Followers: 2)
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: 11)
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: 16)
Electrical and Electronic Engineering     Open Access   (Followers: 23)
Electrical and Power Engineering Frontier     Open Access   (Followers: 23)
Electrical Engineering     Hybrid Journal   (Followers: 19)
Electrical Engineering and Automation     Open Access   (Followers: 7)
Electrical Engineering in Japan     Hybrid Journal   (Followers: 8)
Electrical, Control and Communication Engineering     Open Access   (Followers: 12)
Emerging and Selected Topics in Circuits and Systems     Hybrid Journal   (Followers: 8)
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: 3)
IEEE Access     Open Access   (Followers: 56)
IEEE Electrical Insulation Magazine     Full-text available via subscription   (Followers: 26)
IEEE Signal Processing Magazine     Full-text available via subscription   (Followers: 63)
IEEE Transactions on Control of Network Systems     Hybrid Journal   (Followers: 10)
IEEE Transactions on Dielectrics and Electrical Insulation     Hybrid Journal   (Followers: 13)
IEEE Transactions on Signal and Information Processing over Networks     Full-text available via subscription   (Followers: 7)
IEEJ Transactions on Electrical and Electronic Engineering     Hybrid Journal   (Followers: 14)
IET Control Theory & Applications     Hybrid Journal   (Followers: 21)
IET Electric Power Applications     Hybrid Journal   (Followers: 18)
IET Electrical Systems in Transportation     Hybrid Journal   (Followers: 9)
IETE Journal of Education     Open Access   (Followers: 4)
Indonesian Journal of Electrical Engineering and Computer Science     Open Access   (Followers: 11)
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: 7)
International Journal of Electrical Engineering Education     Hybrid Journal   (Followers: 6)
International Journal of Electrical Power & Energy Systems     Open Access   (Followers: 20)
International Journal of Emerging Electric Power Systems     Hybrid Journal   (Followers: 6)
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: 6)
International Journal of Nuclear Security     Open Access   (Followers: 1)
International Journal on Communication     Full-text available via subscription   (Followers: 12)
International Journal on Control System and Instrumentation     Full-text available via subscription   (Followers: 14)
International Journal on Electrical and Power Engineering     Full-text available via subscription   (Followers: 8)
International Journal on Signal and Image Processing     Full-text available via subscription   (Followers: 4)
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: 10)
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: 16)
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering     Open Access   (Followers: 21)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 7)
Journal of Electrical Systems and Information Technology     Open Access   (Followers: 6)
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: 3)
Jurnal Rekayasa Elektrika     Open Access  
Majlesi Journal of Electrical Engineering     Open Access   (Followers: 1)
Micro and Nano Systems Letters     Open Access   (Followers: 6)
Nanotechnology Development     Open Access   (Followers: 20)
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: 12)
Recent Patents on Electrical & Electronic Engineering     Full-text available via subscription   (Followers: 9)
Recent Patents on Telecommunications     Full-text available via subscription   (Followers: 2)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 4)
Russian Electrical Engineering     Hybrid Journal   (Followers: 4)
SID Symposium Digest of Technical Papers     Hybrid Journal  
Sustainable Energy, Grids and Networks     Hybrid Journal   (Followers: 1)
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  
Trends in Electrical Engineering     Full-text available via subscription   (Followers: 4)
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 the editorial board, current staff, committee members and society officers.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • IEEE Transactions on Sustainable Energy
    • Abstract: Provides a listing of the editorial board, current staff, committee members and society officers.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Information for Authors
    • Abstract: These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • A Hybrid Forecasting Method for Wind Power Ramp Based on Orthogonal Test
           and Support Vector Machine (OT-SVM)
    • Authors: Yongqian Liu;Ying Sun;David Infield;Yu Zhao;Shuang Han;Jie Yan;
      Pages: 451 - 457
      Abstract: In an electric power system with a high penetration of wind power, incoming power ramps pose a serious threat to the power system. To adopt suitable response strategies for wind power ramps, it is important to predict them accurately and in a timely manner. Since power ramps are caused by various factors, their occurrence has irregular characteristics and vary by location, bringing great difficulty in forecasting. To solve this problem, a hybrid forecasting model termed as orthogonal test and support vector machine (OT-SVM) was developed in this paper, which combines an orthogonal test (OT) with a support vector machine (SVM). A novel factor analysis method was established based on the theory of the OT, and applied to determine the optimal inputs of a SVM. The effectiveness of OT-SVM was tested with three wind farms in China, while comparing the results with other related methods. The results show that the proposed OT-SVM has the highest accuracy covering different input numbers and time resolutions. In addition, a novel evaluation index mean accuracy index was proposed, considering both the missed ramps and false ramps, which can be used as a supplementary index for critical success index.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • On the Efficient Calculation of the Periodic Steady-State Response of
           Grid-Connected Wind Parks—Part I
    • Authors: Norberto Garcia;Enrique Acha;
      Pages: 458 - 467
      Abstract: This paper presents a new power systems simulation environment suitable for the swift calculation of the periodic steady-state response of large power networks with large wind parks. In order to achieve the greatest computational efficiency and solution reliability, the wind generator model uses the state-of-the-art voltage-behind-reactance model of the induction generator; in this first part of the paper, the fixed-speed wind generator model is presented. The overall solving environment for the nonlinear system of differential equations representing the power system is the so-called Poincaré map method. A rather useful feature to reduce further the calculation times is the availability of an equivalent wind farm model based on multiple wakes. The Poincaré acceleration yields a vastly improved numerical solution compared to existing models of fixed-speed wind parks. The application of equivalent wind farm models yields a staggering reduction in the elapsed time to only 1.16% of the time demanded by the detailed model, while retaining a good approximation of the response of the wind farm. Full comparisons of the detailed and equivalent wind park models with PSCAD/EMTDC, are carried out and the agreement of the results is excellent. In this paper the emphasis is on harmonic generation.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • A Novel MPPT Algorithm Based on Particle Swarm Optimization for
           Photovoltaic Systems
    • Authors: Ramdan B. A. Koad;Ahmed Faheem Zobaa;Adel El-Shahat;
      Pages: 468 - 476
      Abstract: This paper describes a new maximum-power-point-tracking method for a photovoltaic system based on the Lagrange Interpolation Formula and proposes the particle swarm optimization method. The proposed control scheme eliminates the problems of conventional methods by using only a simple numerical calculation to initialize the particles around the global maximum power point. Hence, the suggested control scheme will utilize less iterations to reach the maximum power point. Simulation study is carried out using MATLAB/SIMULINK and compared with the Perturb and Observe method, the Incremental Conductance method, and the conventional Particle Swarm Optimization algorithm. The proposed algorithm is verified with the OPAL-RT real-time simulator. The simulation results confirm that the proposed algorithm can effectively enhance the stability and the fast tracking capability under abnormal insolation conditions.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Reactive Power Dispatch Method in Wind Farms to Improve the Lifetime of
           Power Converter Considering Wake Effect
    • Authors: Jie Tian;Dao Zhou;Chi Su;Zhe Chen;Frede Blaabjerg;
      Pages: 477 - 487
      Abstract: In wind farms (WF), the most popular and commonly implemented active power control method is the maximum power point tracking (MPPT). Due to the wake effect, the upstream wind turbine (WT) in WFs has more active power generation than the downstream WT at the wind directions and wind speeds that the WF has wake loss. In the case that WTs support the voltage control by reactive power, the upstream WT's power converter may have shorter lifetime even below the industrial standard. In this paper, based on the analysis of the wake effect, the reactive power capability of the doubly fed induction generator (DFIG) WT, and the lifetime of the DFIG WT's power converter, a reactive power dispatch method is proposed in the WF with DFIG WTs to improve the lifetime of the upstream WT's power converter. The proposed reactive power dispatch method is analyzed and demonstrated by the simulation on a WF with 80 DFIG WTs. It can be concluded that, compared with the traditional reactive power dispatch method, the proposed method can increase the lifetime of the upstream WT's power converter.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • An Analysis of Wind Curtailment and Constraint at a Nodal Level
    • Authors: Macarena Martin Almenta;D. John Morrow;Robert J. Best;Brendan Fox;Aoife M. Foley;
      Pages: 488 - 495
      Abstract: Many countries have set challenging wind power targets to achieve by 2020. This paper implements a realistic analysis of curtailment and constraint of wind energy at a nodal level using a unit commitment and economic dispatch model of the Irish Single Electricity Market in 2020. The key findings show that significant reduction in curtailment can be achieved when the system nonsynchronous penetration limit increases from 65% to 75%. For the period analyzed, this results in a decreased total generation cost and a reduction in the dispatch-down of wind. However, some nodes experience significant dispatch-down of wind, which can be in the order of 40%. This work illustrates the importance of implementing analysis at the nodal level for the purpose of power system planning.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Model Predictive Control of Energy Storage Systems for Power Tracking and
           Shaving in Distribution Grids
    • Authors: Alessandro Di Giorgio;Francesco Liberati;Andrea Lanna;Antonio Pietrabissa;Francesco Delli Priscoli;
      Pages: 496 - 504
      Abstract: In this paper, a model predictive control (MPC) strategy is proposed to control the energy flows in a distribution network node (e.g., a distribution substation) equipped with an electric storage system (ESS) and serving a portion of the grid with high penetration of renewable energy sources (RES). The aim is to make the power flow at node level more controllable in spite of the presence of fluctuating distributed energy resources. In particular, the proposed control strategy is such that the controlled power flow at node level tracks the profile established on a day-ahead basis for efficient operation of the grid. That is achieved by letting the MPC controller decide the current storage power setpoint based on the forecasts of the demand and of the RES output. Theoretical results are reported on the stability of the proposed control scheme in a simplified setting foreseeing zero forecasting error. The performance of the system in the general case is then evaluated on a simulation basis. Simulations show the effectiveness in managing RES fluctuations in realistic settings.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Application of Network-Constrained Transactive Control to Electric Vehicle
           Charging for Secure Grid Operation
    • Authors: Junjie Hu;Guangya Yang;Henrik W. Bindner;Yusheng Xue;
      Pages: 505 - 515
      Abstract: This paper develops a network-constrained transactive control method to integrate distributed energy resources (DERs) into a power distribution system with the purpose of optimizing the operational cost of DERs and power losses of the distribution network, as well as preventing grid problems including power transformer congestion and voltage violations. In this method, a price coordinator is introduced to facilitate the interaction between the distribution system operator and the aggregators in the smart grid. Electric vehicles are used to illustrate the proposed network-constrained transactive control method. Mathematical models are presented to describe the operation of the control method. Finally, simulations are presented to show the effectiveness of the proposed method. To guarantee its optimality, we also checked the numerical results obtained with the network-constrained transactive control method and compared them with the one solved by centralized control, and found a good performance of the proposed control method.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Optimization of Charge/Discharge Rates of a Battery Using a Two-Stage
           Rate-Limit Control
    • Authors: Sathish Kumar Kollimalla;Abhisek Ukil;H. B. Gooi;Ujjal Manandhar;Narsa Reddy Tummuru;
      Pages: 516 - 529
      Abstract: Energy storage would play a critical role in the microgrids. In this paper, two-stage variable rate-limit control for battery energy storage is proposed. The objective of this control scheme is to optimize the amount, rate, and time-duration of the energy stored/discharged from the battery. Thus, the battery would charge/discharge at its optimized maximum rate in a hybrid energy storage system. Supercapacitor is used to form the hybrid energy storage system, to complement or supply the energy deficiency during the transient period. With the proposed control scheme, the stress levels on the battery is regulated by optimizing the charge/discharge rates of the battery. The advantages of the proposed control scheme also includes maintaining the state of charge of the battery within the limits for longer duration. This control scheme is validated using real-time control hardware in loop using OPAL-RT and dSPACE.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Risk Adjustable Day-Ahead Unit Commitment With Wind Power Based on Chance
           Constrained Goal Programming
    • Authors: Yang Wang;Shuqiang Zhao;Zhi Zhou;Audun Botterud;Yan Xu;Runze Chen;
      Pages: 530 - 541
      Abstract: The impact of wind power forecast uncertainty has been amplified by the deepening wind power penetration. To guarantee system security and reliability, sufficient dispatchable generation and transmission capacities have to be reserved. Currently, research has been carried out to improve system operational performance by optimizing schedules considering uncertainty. However, most methods are designed to cover a given risk level of uncertainty, which is determined ex ante. With the increase in wind power capacity, defining the risk level a priori without considering the unit commitment (UC) may limit the scheduling efficiency. Essentially, there is no absolute standard for acceptable risk exposure. Instead, there is a tradeoff between the risk and the cost of reserve capacity. Therefore, it is necessary to develop a tool to enable a flexible and comprehensive consideration of the risk level. In this paper, by combining chance constrained programming and goal programming, a novel model based on chance constrained goal programming is proposed to optimize the risk adjustable UC problem. To facilitate an efficient solution, the proposed model is transferred into a tractable mixed integer linear programming problem by a deterministic equivalent and piecewise linearization. Case studies are performed on an IEEE 118-bus system to illustrate the effectiveness and efficiency of the model.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Optimization and Reliability Evaluation of an Offshore Wind Farm
    • Authors: Ouahid Dahmani;Salvy Bourguet;Mohamed Machmoum;Patrick Guerin;Pauline Rhein;Lionel Josse;
      Pages: 542 - 550
      Abstract: This paper presents an original approach aiming to obtain the optimum configuration of an offshore wind farm (OWF). Thanks to cost models, we take into account the costs off all the parts of the electrical network. The optimization platform, based on a genetic algorithm, also allows us to evaluate the reliability of an OWF. This approach is used to compare the topologies obtained in different cases on a real OWF, the “Banc de Guerande.” The selected design of the OWF is compared to the results obtained using different methods: cost optimization, or both cost and reliability optimization. The optimization results show that the ring topologies give interesting results if the total cost including the expected energy not supplied during the lifetime of the OWF are taken into account. The number of offshore substations and their positions are also considered in the optimization: we show that the introduction of more substations in order to obtain better performances is possible at a reasonable cost. The presented optimization tool can help to design such farms taking into account several constraints.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • A Probabilistic Competitive Ensemble Method for Short-Term Photovoltaic
           Power Forecasting
    • Authors: Antonio Bracale;Guido Carpinelli;Pasquale De Falco;
      Pages: 551 - 560
      Abstract: Photovoltaic systems are expected to play a key role in the planning and operation of future distribution systems due to the benefits associated with their use. Unfortunately, a great problem is involved in photovoltaic power utilization, i.e., the unpredictability of the solar source. Thus, many forecasting methods have been developed in order to provide tools with adequate consistency, quality, and value. The methods can provide either deterministic or probabilistic forecasts; the latter seem to be the most appropriate for taking into account the unavoidable uncertainties of the solar source. In this paper, a new probabilistic method based on a competitive ensemble of different base predictors is proposed for the short-term forecasting of photovoltaic power. Three probabilistic methods were selected and trained as base predictors in order to obtain an ensemble of the predictive distribution with optimal characteristics of sharpness and reliability. Numerical applications based on actual data were performed to test the effectiveness of the proposed method with respect to single predictors and to a benchmark method.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • A Robust Backstepping High-Order Sliding Mode Control Strategy for
           Grid-Connected DG Units With Harmonic/Interharmonic Current Compensation
    • Authors: Nima Mahdian Dehkordi;Nasser Sadati;Mohsen Hamzeh;
      Pages: 561 - 572
      Abstract: This paper presents a new nonlinear current control strategy based on backstepping control and high-order sliding mode differentiator in order to employ distributed generation (DG) unit interfacing converters to actively compensate harmonics/interharmonics of local loads. The converter-based DG unit is connected to a weak grid (with uncertain impedance) and local load (that can be parametrically uncertain and topologically unknown) through an LCL filter. The proposed strategy robustly regulates the inverter output currents and delivers pure sinusoidal, three-phase balanced currents to the grid. The new controller demonstrates the robust performance and robust stability of the DG unit system with respect to the filter parameters uncertainties, grid impedance, grid frequency, and grid voltage as well as the unknown load dynamics that include unbalanced loads and nonlinear loads with harmonic and interharmonic currents. We should remark that the local compensation of the loads with interharmonic current using a DG unit system is first proposed in this paper. When compared with the popular parallel proportional resonant control technique, the proposed controller offers smoother transient responses and a lower level of current distortion. The performance of the proposed control strategy is verified in MATLAB/SimPowerSystems toolbox.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Power Ramp Limitation Capabilities of Large PV Power Plants With Active
           Power Reserves
    • Authors: Bogdan-Ionuţ Crăciun;Tamás Kerekes;Dezső Séra;Remus Teodorescu;Udaya Deepa Annakkage;
      Pages: 573 - 581
      Abstract: Power ramp limitation (PRL) is likely to become a requirement for large-scale photovoltaic power plants (LPVPPs) in order to allow the increase of PV penetration levels. Especially in islands with reduced inertia capability, this problem is more stringent: high-power ramp can be caused by either fast irradiance changes or other participant generators for example wind power, or loads. In order to compensate for the power mismatch, LPVPPs must use active power reserve (APR), by either curtailment or auxiliary storage. The paper proposes a PRL control structure for dynamic APR sizing and deployment. The selected test case is the power system of Puerto Rico (PREPA), modeled using the modified IEEE 12 bus benchmark system, with different levels of PV penetration. It is shown that LPVPP with PRL can effectively reduce the ramping rate of the participating generators. Considering that the large area of LPVPPs acts as a filter against fast irradiance changes, the study also reveals the required plant size for which an auxiliary storage is no longer needed in order to comply with PRL requirements-an important economical aspect.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • A Hybrid Algorithm for Short-Term Solar Power Prediction—Sunshine
           State Case Study
    • Authors: Arash Asrari;Thomas X. Wu;Benito Ramos;
      Pages: 582 - 591
      Abstract: The growing rate of the integration of photovoltaic (PV) sites into the structure of power systems makes the task of solar power prediction more important in order to control the power quality and improve the reliability of system. In this paper, a hybrid forecasting algorithm is proposed for hour-ahead solar power prediction. A combination of gradient-descent optimization and meta-heuristic optimization approaches are designed in the structure of the presented model to take into account the prediction accuracy as well as the computational burden. At the first step, the gradient-descent optimization technique is employed to provide the initial parameters of a feedforward artificial neural network (ANN). At the next step, the meta-heuristic optimization model, called shuffled frog leaping algorithm (SFLA), is developed to search for the optimal set of parameters of ANN using the initial individuals found by the gradient-descent optimization. Then, the identified parameters by the customized SFLA will be employed by the ANN for short-term solar power prediction. The performance of the proposed forecasting algorithm is demonstrated on the solar power data of three simulated PV sites in Florida for 2006.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Operational Planning of Electric Vehicles for Balancing Wind Power and
           Load Fluctuations in a Microgrid
    • Authors: Hongming Yang;Hao Pan;Fengji Luo;Jing Qiu;Youjun Deng;Mingyong Lai;Zhao Yang Dong;
      Pages: 592 - 604
      Abstract: The intermittency of renewable energy poses challenges on the reliable and economical operations of microgrids. This paper considers a grid-connected microgrid model which consists of a logistics distribution system, where electric vehicles (EVs) depart from the depot, deliver the goods to multiple demand loads, and then, return to the depot. Based on this, this paper studies the coordinated dispatch strategies of EVs to smooth renewable energy and load fluctuations of the microgrid while ensuring the quality of logistics services. A microgrid operation model is proposed to optimize the driving routes, fast-charging time, and regular-charging/discharging strategies of EVs. Specifically, the objective is to minimize the overall operation cost of the microgrid while satisfying the requirements of the logistics distribution tasks. A self-adaptively imperialist competitive algorithm is proposed to solve the model. The simulation results demonstrate the effectiveness of the proposed model.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Power Sharing Control Strategy of Multiterminal VSC-HVDC Transmission
           Systems Utilizing Adaptive Voltage Droop
    • Authors: Mohamed Abdelaziz Abdelwahed;Ehab F. El-Saadany;
      Pages: 605 - 615
      Abstract: This paper presents an adaptive droop-based power-sharing control strategy. The primary objective is to control the sharing of the active power transmitted by a multiterminal voltage-source converter based high voltage direct current network among a number of onshore ac grids or offshore loads based on the desired percentage shares. The shared power is generated by remote generation plants (e.g., offshore wind farms) or is provided as surplus from ac grids. The desired percentage shares of active power are optimized by the system operator in order to fulfil the active power requirements of the connected grids with respect to meeting goals such as supporting energy adequacy, increasing renewable energy penetration, and minimizing losses. The control strategy is based on two hierarchal levels: voltage-droop control as the primary controller and an optimal-power flow based secondary (supervisory) controller for selecting the optimal droop reference voltages. Based on the dc voltage transient and steady-state dynamics, a methodology for choosing the droop gains for droop controlled converters has been developed. The proposed control strategy has been validated through simulation on the CIGRE B4 dc grid test system. The results confirmed the flexibility and effectiveness of the power-sharing control provided by the new control strategy.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Electric Vehicle Charging Facility as a Smart Energy Microhub
    • Authors: Walied Alharbi;Kankar Bhattacharya;
      Pages: 616 - 628
      Abstract: This paper presents a novel framework for designing an electric vehicle charging facility (EVCF) as a smart energy microhub from the perspectives of both an investor and a local distribution company. The proposed framework includes a vehicle decision tree, a queuing model, a distribution margin assessment model, a distributed generation (DG) penetration assessment model, an economic assessment model, and a distribution operations model. Three design options for the EVCF are examined; battery energy storage systems (BESS), renewables based DG, and a microhub that incorporates both BESS and renewables-based DG with the option of exchanging power with the main grid. Test results considering a 33 bus distribution system and realistic vehicle statistics extracted from the 2009 (US) National Household Travel Survey are presented and discussed. The findings demonstrate the effectiveness of the proposed smart energy microhub design framework.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • A Wind Farm Reliability Model Considering Both Wind Variability and
           Turbine Forced Outages
    • Authors: Samer Sulaeman;Mohammed Benidris;Joydeep Mitra;Chanan Singh;
      Pages: 629 - 637
      Abstract: This paper presents an analytical method to model the output of large wind farms for power system reliability assessment. The model considers the variability of wind, random failures (forced outages) of turbines, as well as the correlation between turbine outputs that results from the turbines on a farm being subjected to similar incident wind speeds. Due to this correlation, the outputs of individual turbines cannot be modeled as independent random variables. The problem is addressed here by separately modeling the independent outages of wind turbines and the dependency on wind speed, and then convolving the two distributions. The resulting model includes both probability and frequency distributions of the power output of the wind farm. The proposed method is demonstrated on the IEEE Reliability Test System. Monte Carlo simulation is used to validate the results.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Offshore Wind Farm Layout Design Considering Optimized Power Dispatch
    • Authors: Peng Hou;Weihao Hu;Mohsen Soltani;Cong Chen;Baohua Zhang;Zhe Chen;
      Pages: 638 - 647
      Abstract: Offshore wind farm has drawn more and more attention recently due to its higher energy capacity and more freedom to occupy area. However, the investment is higher. In order to make a cost-effective wind farm, the wind farm layout should be optimized. The wake effect is one of the dominant factors leading to energy losses. It is expected that the optimized placement of wind turbines (WT) over a large sea area can lead to the best tradeoff between energy yields and capital investment. This paper proposes a novel way to position offshore WTs for a regular shaped wind farm. In addition to optimizing the direction of wind farm placement and the spacing between WTs, the control strategy's impact on energy yields is also discussed. Since the problem is nonconvex and lots of optimization variables are involved, an evolutionary algorithm, the particle swarm optimization algorithm, is adopted to find the solution. In order to increase the probability of finding the global optimal solution, the adaptive parameter control strategy is utilized. Simulation results are given to verify the proposed approach and comparison is made with results obtained using other methods.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • A Hybrid Simulation Tool for the Study of PV Integration Impacts on
           Distribution Networks
    • Authors: Ali Hariri;Md. Omar Faruque;
      Pages: 648 - 657
      Abstract: This paper introduces a hybrid simulation tool that is used to study the impacts of integration of photovoltaic (PV) systems on distribution networks. The tool is composed of an electromagnetic transient (EMT) simulation tool interfaced with an open-source phasor analysis tool, OpenDSS. The purpose of this tool is to provide detailed modeling along with fast and accurate simulation of electric systems with interconnected PV systems. The developed tool models the PV energy system using detailed EMTP-type algorithms, while the rest of the distribution system is modeled in phasor domain using OpenDSS. This paper demonstrates some of the functions, applications, and advantages of the hybrid tool. The tool has been tested with a real Florida-based distribution feeder with multiple PV energy systems. A full EMT model of the feeder has been developed in SimPowerSystems to compare and validate the results. The results suggest that the hybrid tool offers significant benefits and functionality over OpenDSS.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Robust Co-Optimization Scheduling of Electricity and Natural Gas Systems
           via ADMM
    • Authors: Chuan He;Lei Wu;Tianqi Liu;Mohammad Shahidehpour;
      Pages: 658 - 670
      Abstract: The significant growth of gas-fired power plants and emerging power-to-gas (PtG) technology has intensified the interdependency between electricity and natural gas systems. This paper proposes a robust co-optimization scheduling model to study the coordinated optimal operation of the two energy systems. The proposed model minimizes the total costs of the two systems, while considering power system key uncertainties and natural gas system dynamics. Because of the limitation on exchanging private data and the challenge in managing complex models, the proposed co-optimization model is tackled via alternating direction method of multipliers (ADMM) by iteratively solving a power system subproblem and a gas system subproblem. The power system subproblem is solved by column-and-constraint generation (C&CG) and outer approximation (OA), and the nonlinear gas system subproblem is solved by converting into a mixed-integer linear programming model. To overcome nonconvexity of the original problem with binary variables, a tailored ADMM with a relax-round-polish process is developed to obtain high-quality solutions. Numerical case studies illustrate the effectiveness of the proposed model for optimally coordinating electricity and natural gas systems with uncertainties.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Quantification of Intra-hour Security-Constrained Flexibility Region
    • Authors: Zhijun Qin;Yunhe Hou;Shunbo Lei;Feng Liu;
      Pages: 671 - 684
      Abstract: Rapid growth of renewable energy sources (RES) in the generation capacity mix poses substantial challenges on the operation of power systems in various time scales. Particularly in the intra-hour time scale, the interplay among variability and uncertainty of RES, unexpected transmission/generation outages, and short dispatch lead time cause difficulties in generation-load balancing. This paper proposes a method to quantify the intra-hour flexibility region. A robust security-constrained multiperiod optimal power flow model is first constructed to quantify the frequency, magnitude, and intensity of insufficient flexibility. The randomness of RES is captured by uncertainty sets in this model. The N-k contingency, spinning reserve, and corrective control limit constraints are included. This model is then cast into a two-stage robust optimization model and solved by the column-and-constraint generation method. The emergency measures with a least number of affected buses are derived and subsequently assessed by the post-optimization sensitivity analysis. Finally, the operational flexibility region is determined by continuous perturbation on the RES penetration level and the forecast error. The IEEE 14-bus system and a realistic Chinese 157-bus system are used to demonstrate the proposed method.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Maximum Power Point Tracking of a Wind Power Plant With Predictive
           Gradient Ascent Method
    • Authors: Chunghun Kim;Yonghao Gui;Chung Choo Chung;
      Pages: 685 - 694
      Abstract: In this paper, we present maximum power point tracking for a wind power plant (WPP) using the gradient ascent (GA) in a data-driven manner. The conventional GA method achieves fast convergent performance by considering only direct wake terms when calculating the axial induction factors. However, the conventional method might not be close to optimal even when the wind conditions are steady state. In this paper, we propose a new method using the relationships between the direct and indirect wake terms. Using the relationship between the wake terms can prevent sudden deviations after convergence to a single operating point, even when significant indirect wake terms exist in the presence of multiple wakes. Therefore, the proposed method provides not only fast convergence to an operating point, but also closer-to-optimal power production without sudden deviations compared to the conventional method. We validated the effectiveness of the proposed method using modeled WPP layouts with various wind conditions.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Battery ESS Planning for Wind Smoothing via Variable-Interval Reference
           Modulation and Self-Adaptive SOC Control Strategy
    • Authors: Feng Zhang;Ke Meng;Zhao Xu;Zhaoyang Dong;Li Zhang;Can Wan;Jun Liang;
      Pages: 695 - 707
      Abstract: The variability of wind power generation increases the uncertainties in modern power system, affecting its physical operation. Owning to the fast response capability, battery energy storage system (BESS) has offered an answer to this problem. In this paper, a novel sizing methodology is proposed for BESS planning, which strikes a balance between economic cost and wind smoothing performance. First, a novel variable-interval reference signal optimization approach and a fuzzy control-based charging/discharging scheme are presented to smooth wind power, maintaining the state-of-health of BESS in the meanwhile. And then, power and energy capacities are determined according to a statistical model of charge/discharge power and the economic cost model, respectively. Finally, case studies are carried out to demonstrate the performance of the proposed method. The impact from wind power forecasting error during real-time operation is also analyzed.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Modeling Uncertainty in Tidal Current Forecast Using Prediction
           Interval-Based SVR
    • Authors: Abdollah Kavousi-Fard;
      Pages: 708 - 715
      Abstract: This paper proposes a prediction interval-based model for modeling the uncertainties of tidal current prediction. The proposed model constructs the optimal prediction intervals (PIs) based on support vector regression (SVR) and a nonparametric method called a lower upper bound estimation (LUBE) method. In order to increase the modeling stability of SVRs that are used in the LUBE method, the idea of combined prediction intervals is employed. As the optimization tool, a flower pollination algorithm along with a two-phase modification method is presented to optimize the SVR parameters. The proposed model employs fuzzy membership functions to provide appropriate balance between the PI coverage probability (PICP) and PI normalized average width (PINAW), independently. The performance of the proposed model is examined on the practical tidal current data collected from the Bay of Fundy, NS, Canada.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Cost-Constrained Dynamic Optimal Electric Vehicle Charging
    • Authors: Maigha;M. L. Crow;
      Pages: 716 - 724
      Abstract: Electric vehicles are an integral component of an environmentally sustainable and resilient infrastructure. Successful penetration of electric vehicles requires close coupling between the customers and load serving entities, adaptive energy markets, and technological advancements. In this paper, distribution line over-loading due to vehicle charging has been mitigated using both day-ahead (static) and real-time (dynamic) frameworks, using continuous and discrete charging rates. The proposed solution focuses on valley filling (system perspective) and charging cost reduction (customer perspective). The real-time solution was achieved using a moving horizon optimization technique. In addition to providing charging coordination, the impacts of two different pricing structures were analyzed to ascertain the customer's individual cost optima with respect to the system optima. The results presented strongly indicate that a global pricing structure will not be optimal for all consumers due to their diverse driving habits.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Variable Generation Power Forecasting as a Big Data Problem
    • Authors: Sue Ellen Haupt;Branko Kosović;
      Pages: 725 - 732
      Abstract: To blend growing amounts of power from renewable resources into utility operations requires accurate forecasts. For both day ahead planning and real-time operations, the power from the wind and solar resources must be predicted based on real-time observations and a series of models that span the temporal and spatial scales of the problem, using the physical and dynamical knowledge as well as computational intelligence. Accurate prediction is a Big Data problem that requires disparate data, multiple models that are each applicable for a specific time frame, and application of computational intelligence techniques to successfully blend all of the model and observational information in real-time and deliver it to the decision makers at utilities and grid operators. This paper describes an example system that has been used for utility applications and how it has been configured to meet utility needs while addressing the Big Data issues.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Optimal Energy Storage Siting and Sizing: A WECC Case Study
    • Authors: Ricardo Fernández-Blanco;Yury Dvorkin;Bolun Xu;Yishen Wang;Daniel S. Kirschen;
      Pages: 733 - 743
      Abstract: The large-scale integration of a grid-scale energy storage and the increasing penetration of renewable resources motivate the development of techniques for determining the optimal ratings and locations of storage devices. This paper proposes a method for identifying the sites where energy storage systems should be located to perform spatio-temporal energy arbitrage most effectively and the optimal size of these systems. This method takes a centralized perspective where the objective is to minimize the sum of the expected operating cost and the investment cost of energy storage. It has been tested on a realistic 240-bus 448-line model of the Western Electricity Coordinating Council (WECC) interconnection. The influence on the results of the following parameters is analyzed: Maximum number of storage locations, maximum size of storage systems, capital cost of deploying storage, value assigned to spillage of renewable energy, marginal cost of conventional generation, and renewable generation capacity. These numerical results are used to characterize the benefits that energy storage can provide in prospective large-scale power systems with renewable generation.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • A Two-Stage Robust Optimization for Centralized-Optimal Dispatch of
           Photovoltaic Inverters in Active Distribution Networks
    • Authors: Tao Ding;Cheng Li;Yongheng Yang;Jiangfeng Jiang;Zhaohong Bie;Frede Blaabjerg;
      Pages: 744 - 754
      Abstract: Optimally dispatching photovoltaic (PV) inverters is an efficient way to avoid overvoltage in active distribution networks, which may occur in the case of the PV generation surplus load demand. Typically, the dispatching optimization objective is to identify critical PV inverters that have the most significant impact on the network voltage level. Following, it ensures the optimal set-points of both active power and reactive power for the selected inverters, guaranteeing the entire system operating constraints (e.g., the network voltage magnitude) within reasonable ranges. However, the intermittent nature of solar PV energy may affect the selection of the critical PV inverters and also the final optimal objective value. In order to address this issue, a two-stage robust centralized-optimal dispatch model is proposed in this paper to achieve a robust PV inverter dispatch solution considering the PV output uncertainties. In addition, the conic relaxation-based branch flow formulation and the column-and-constraint generation algorithm are employed to deal with the proposed robust optimization model. Case studies on a 33-bus distribution network and comparisons with the deterministic optimization approach have demonstrated the effectiveness of the proposed method.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • A Single-Stage Stand-Alone Photovoltaic Energy System With High Tracking
    • Authors: Hadeed Ahmed Sher;Arslan Abbas Rizvi;Khaled E. Addoweesh;Kamal Al-Haddad;
      Pages: 755 - 762
      Abstract: A single-stage flyback PV inverter with maximum power point tracking (MPPT) high-speed capability is presented in this paper. The proposed stand-alone photovoltaic energy system (SAPES) incorporates the use of hybrid MPPT to ensure peak energy harvesting under all weather conditions. The proposed hybrid MPPT method combines the conventional short current pulse (SCP) MPPT method and the perturb and observe (P&O) methods. Measurement of the offline parameter [short-circuit current of PV module (Is,)] for SCP is made on the basis of the difference between the offline parameter and the instantaneous current of PV module (Ipv). Use of a single power conversion stage is achieved by employing a modified flyback inverter operating in a discontinuous-conduction mode. The control structure of the conventional flyback inverter is also modified to incorporate the hybrid MPPT algorithm. The proposed SAPES method is tested using computer-aided simulations and real-time hardware in the loop experimentation using the dSPACE DS1104 board. The results obtained using the proposed systems are better than those for the conventional algorithms under the environmental conditions tested.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Two-Stage Compensation Algorithm for Dynamic Economic Dispatching
           Considering Copula Correlation of Multiwind Farms Generation
    • Authors: Min Xie;Jing Xiong;Shaojia Ke;Mingbo Liu;
      Pages: 763 - 771
      Abstract: The dynamic economic dispatching of power system connected with multiple wind farms is a typical stochastic programming problem. How to model the randomness of wind power and how to solve this complex stochastic optimization problem are the key points. In this paper, copula theory is used to formulate the correlation of multiwind farms generation. Then, the dynamic economic dispatching model is founded with the fuel consumption, gas pollution emission fees, and electricity purchase costs as the optimized objective. The two-stage compensation algorithm is then introduced to solve the dispatching problem. In this algorithm, the conventional (nonstochastic) decision variables and stochastic variables are decoupled, which separate the dynamic dispatching model into two stage modes. The optimal dispatching result is worked out by iteration between the two stage models. Case studies on IEEE118-bus system and an actual provincial power grid show that the proposed algorithm can drastically reduce computational burden, and satisfy the actual requirements of engineering practice.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • DC Grid Voltage Regulation Using New HESS Control Strategy
    • Authors: Sathish Kumar Kollimalla;Mahesh K. Mishra;Abhisek Ukil;H. B. Gooi;
      Pages: 772 - 781
      Abstract: The power generation from renewable power sources is variable in nature, and may contain unacceptable fluctuations in case of the wind power generation. High fluctuations in power generation may negatively impact the voltage stability of the microgrid. This problem can be alleviated by using hybrid energy storage system consisting of batteries and supercapacitors (SCs) at dc grid. A new control scheme is proposed to control the power sharing between batteries and SCs to match the generation-demand mismatch and hence to regulate the grid voltage. In the proposed control strategy, the SC supplies error component of the battery current in addition to the fast transient power demand. This added feature not only improves the dc grid voltage regulation capability but also reduces the stress levels on the battery and hence increases the life span of the battery. The main advantage of the scheme is that, the uncompensated power due to slow dynamics of the battery is diverted to the SC and keeps the state of charge within the limits for longer duration, as compared to the conventional strategy. The proposed scheme is validated through detailed experimental studies.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Fuzzy Energy and Reserve Co-optimization With High Penetration of
           Renewable Energy
    • Authors: Cong Liu;Audun Botterud;Zhi Zhou;Pengwei Du;
      Pages: 782 - 791
      Abstract: In this paper, we propose a fuzzy-based energy and reserve co-optimization model with consideration of high penetration of renewable energy. Under the assumption of a fixed uncertainty set of renewables, a two-stage robust model is proposed for clearing energy and reserves in the first stage and checking the feasibility and robustness of re-dispatches in the second stage. Fuzzy sets and their membership functions are introduced into the optimization model to represent the satisfaction degree of the variable uncertainty sets. The lower bound of the uncertainty set is expressed as fuzzy membership functions. The solutions are obtained by transforming the fuzzy mathematical programming formulation into traditional mixed integer linear programming problems.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Distributed MPC-Based Secondary Voltage Control Scheme for Autonomous
           Droop-Controlled Microgrids
    • Authors: Guannan Lou;Wei Gu;Yinliang Xu;Ming Cheng;Wei Liu;
      Pages: 792 - 804
      Abstract: In this study, we propose a novel distributed secondary control scheme for both voltage and frequency in autonomous microgrids. By incorporating predictive mechanisms into distributed generations, the secondary voltage control is converted to a tracker consensus problem of distributed model predictive control, with the synchronous convergence procedure for voltage magnitudes to the reference value drastically accelerated at a low communication cost. A sufficient local stability condition with the parameter analysis is established. Thus, a distributed proportional integral method combined with a finite-time observer to estimate the global reference information is presented in the frequency restoration while maintaining accurate active power sharing. Our approach accommodates model uncertainty, plug-and-play capability, and especially robustness against information update intervals, which is essential when the conventional method probably yields toward a poor performance. Meanwhile, the distributed architecture implemented on the local and neighboring information allows for a sparse communication network and eliminates the requirement for a centralized controller. Simulation results are provided to verify the effectiveness of the proposed control methodology.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Shuffled Complex Evolution on Photovoltaic Parameter Extraction: A
           Comparative Analysis
    • Authors: Ruan Carlos Marques Gomes;Montiê Alves Vitorino;Maurício Beltrão de Rossiter Corrêa;Darlan Alexandria Fernandes;Ruxi Wang;
      Pages: 805 - 815
      Abstract: This paper proposes a method for extracting the intrinsic parameters of a photovoltaic (PV) generator by using shuffled complex evolution (SCE) technique for a double-diode PV model. The characteristic equation of a double-diode PV presents a nonlinear behavior and the determination of the intrinsic parameters from a I × V experimental curve requires the use of nonlinear optimization methods. To evaluate the accuracy of the SCE technique for extracting the intrinsic PV parameters, a comparison with other well-known methods is presented; in particular, analytic method, Levenberg-Marquardt, genetic algorithms (GA), differential evolution (DE), and particle swarm optimization (PSO) are considered. This comparison is performed by using statistical analysis and by estimating the relative error of parameter values; it has been applied to an unknown PV module and to a known PV cell. The obtained results showed that, compared with other evolutionary methods (GA, DE and PSO), the SCE presents the lowest computational time and requires less iterations/generations to converge. All the results prove that the proposed method is feasible, faster, and presents better results than the conventional ones.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • $mathrm{H}_{infty}$ Robust Current Control for DFIG-Based Wind Turbine
           Subject to Grid Voltage Distortions
    • Authors: Yun Wang;Qiuwei Wu;Wenming Gong;Mikkel Peter Sidoroff Gryning;
      Pages: 816 - 825
      Abstract: This paper proposes an H∞ robust current controller for doubly-fed induction-generator (DFIG)-based wind turbines subject to grid voltage distortions. The controller is to mitigate the impact of the grid voltage distortions on rotor currents with DFIG parameter perturbation. The grid voltage distortions considered include asymmetric voltage dips and grid background harmonics. An uncertain DFIG model is developed with uncertain factors originating from distorted stator voltage, and changed generator parameters due to the flux saturation effect, the skin effect, etc. Weighting functions are designed to efficiently track the unbalanced current components and the fifth and seventh background harmonics. The robust stability and robust performance of the proposed controller are verified by the structured singular value μ. The performance of the H∞ robust current controller was demonstrated with a 1.5-MW DFIG model, showing its harmonics suppression ability with DFIG parameter perturbation and improved robustness.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Robust Integration of High-Level Dispatchable Renewables in Power System
    • Authors: Hongxing Ye;Jianhui Wang;Yinyin Ge;Jia Li;Zuyi Li;
      Pages: 826 - 835
      Abstract: The increasing penetration of renewable energy sources (RES) requires more flexibility resources (FR), such as thermal units and storages. FR kept in the system can help accommodate the uncertainties from RES. The challenge is how the system can survive when the RES level is very high. In this paper, RESs are considered as full-role market participants. They can bid in the day-ahead market, and the powers they deliver to the market are controllable up to their maximum available powers. Therefore, RESs are effectively dispatchable and can function as FR. To integrate dispatchable renewables, a two-stage robust unit commitment (UC) and dispatch model is established. In the first stage, a base UC and dispatch is determined. In the second stage, all FRs including RESs are used to accommodate the uncertainties, which is a mixed-integer programming (MIP) problem. It is proved that the solution to the max-min problem can be identified directly whether the strong duality holds or not for the inner minimization problem. The solution robustness can be guaranteed by considering only one extra scenario. Numerical results show the effectiveness of the proposed model and its advantages over the traditional robust UC model with high-level RES penetration.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • A Real-Time Multistep Optimization-Based Model for Scheduling of
           Storage-Based Large-Scale Electricity Consumers in a Wholesale Market
    • Authors: Hadi Khani;Rajiv K. Varma;Mohammad R. Dadash Zadeh;Amir H. Hajimiragha;
      Pages: 836 - 845
      Abstract: A new real-time optimal scheduling model is proposed and analyzed in this paper to aggregate storage benefits for a large-scale electricity consumer. The complete model for optimal operation of storage-based electrical loads considering both the capital and operating expenditures of storage is developed. A real-time load forecaster is incorporated into the optimal scheduling algorithm using soft constraints, slack variables, and penalizing mechanisms. The application of the proposed model to a real-world large-scale electricity consumer is examined and compared with previous models. It is demonstrated that the proposed model outperforms prior models by generating higher profitability of investment in storage, lower storage operating expenditure, and an extended life of the storage plant.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Identifying Optimal Energy Flow Solvability in Electricity-Gas Integrated
           Energy Systems
    • Authors: Sheng Chen;Zhinong Wei;Guoqiang Sun;Kwok W. Cheung;Dan Wang;
      Pages: 846 - 854
      Abstract: Significant growth in gas-fired generator use has strengthened the interdependence between the electrical power systems and the natural gas systems. It is therefore imperative to analyze both systems jointly as an electricity-gas integrated energy system (IES). However, peak electricity and gas demands, intermittent renewable- resource power generation, and severe contingencies can result in an unsolvable optimal energy flow (OEF). Unsolvable OEF poses a serious threat to IES because a secure operating condition is unavailable without corrective controls. Thereby, this paper proposes three models for identifying OEF solvability. Model I minimizes the square of the energy flow mismatches, and Model II maximizes the loadability. Both Models I and II add slack variables to equality constraints, while Model III relaxes inequality constraints. Meanwhile, bidirectional gas flow models are employed. Based on Models I-III, the OEF feasibility margin and the infeasibility degree are defined. Case studies integrate an IEEE 39-node system and a 48-node gas network for validating the proposed models.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Impacts of Operational Variability and Uncertainty on Distributed
           Generation Investment Planning: A Comprehensive Sensitivity Analysis
    • Authors: Sergio F. Santos;Desta Z. Fitiwi;Abebe W. Bizuayehu;Miadreza Shafie-khah;Miguel Asensio;Javier Contreras;Carlos M. P. Cabrita;João P. S. Catalão;
      Pages: 855 - 869
      Abstract: This paper presents a comprehensive sensitivity analysis to identify the uncertain parameters which significantly influence the decision-making process in distributed generation (DG) investments and quantify their degree of influence. To perform the analysis, a DG investment planning model is formulated as a novel multistage and multiscenario optimization problem. Moreover, to ensure tractability and make use of exact solution methods, the entire problem is kept as a mixed-integer linear programming optimization. A real-world distribution network system is used to carry out the analysis. The results of the analysis generally show that uncertainty as well as operational variability of the considered parameters have meaningful impacts on investment decisions of DG. The degree of influence varies from one parameter to another. But, in general, ignoring or inadequately considering uncertainty and variability in model parameters has a quantifiable cost. Hence, the analysis made in this paper can be very useful to identify the most relevant model parameters that need special attention in planning practices.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • A Novel State of Charge Feedback Strategy in Wind Power Smoothing Based on
           Short-Term Forecast and Scenario Analysis
    • Authors: Yun Zhou;Zheng Yan;Naihu Li;
      Pages: 870 - 879
      Abstract: The battery energy storage system (BESS)-integrated wind farm (WF) has been widely proposed in the literature to reduce the variability of wind power generation. The state of charge (SOC) feedback strategy is a basic and important strategy to keep the SOC of BESS within its proper range while BESS smoothing out the fluctuations of the WF. In this paper, a novel SOC feedback strategy in wind power smoothing based on short-term forecast and scenario analysis is proposed. Other than mainly considering the real-time information in existing strategies, the principal idea of the new SOC feedback strategy is to estimate the SOC varying curve of the BESS in the advance control period with the assistance of the forecasted wind power data. Dynamic SOC margins are determined by scenario analysis to handle the uncertainty in wind power forecast. When the BESS suffers from over-charge or over-discharge in the advance control period, the SOC feedback strategy is then triggered to adjust the BESS output at the current control moment. The effectiveness of the new SOC feedback strategy is validated in case study by using historical wind power data of a WF in Gansu province of China.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Parallel Wind Turbine Powertrains and Their Design for High Availability
    • Authors: Alasdair McDonald;Godwin Jimmy;
      Pages: 880 - 890
      Abstract: Conventional wind turbine powertrains tend to use single-input-single-output topologies (i.e., one gearbox coupled to a generator with a power converter). Here, powertrains with single-input-multiple-output subsystems are analyzed with Markov state space models in order to quantify any improvements in the availability. A baseline powertrain's availability and that of different parallel powertrains are evaluated using wind turbine powertrain failure and repair rate data. The results show that an increase in the number of parallel systems N does not automatically lead to a higher availability for a wind turbine powertrain; however, when failure and repair rates scale with module power ratings then there is an improvement. The designer can further improve the availability by over-rating each parallel module. The net benefit of parallel powertrains depends both on the turbine and the type of powertrain technology.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • Introducing the IEEE PES Resource Center
    • Pages: 891 - 891
      Abstract: Advertisement, IEEE.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
  • I am investing in tomorrow Are you?
    • Pages: 892 - 892
      Abstract: Advertisement, IEEE.
      PubDate: April 2017
      Issue No: Vol. 8, No. 2 (2017)
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