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Actuators     Open Access  
Advances in Electrical Engineering     Open Access   (Followers: 5)
Advances in Microelectronic Engineering     Open Access   (Followers: 2)
Advances in Signal Processing     Open Access   (Followers: 2)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 12)
American Journal of Sensor Technology     Open Access   (Followers: 1)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 6)
Archives of Control Sciences     Open Access   (Followers: 2)
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Atom Indonesia     Open Access   (Followers: 1)
Bulletin of Electrical Engineering and Informatics     Open Access   (Followers: 9)
Circuits, Systems, and Signal Processing     Hybrid Journal   (Followers: 9)
Computers & Electrical Engineering     Hybrid Journal   (Followers: 9)
Current Trends in Signal Processing     Full-text available via subscription   (Followers: 2)
Electric Power Components and Systems     Hybrid Journal   (Followers: 8)
Electric Power Systems Research     Partially Free   (Followers: 13)
Electrical and Electronic Engineering     Open Access   (Followers: 12)
Electrical and Power Engineering Frontier     Open Access   (Followers: 10)
Electrical Engineering     Hybrid Journal   (Followers: 15)
Electrical Engineering and Automation     Open Access   (Followers: 2)
Electrical Engineering in Japan     Hybrid Journal   (Followers: 7)
Electrical, Control and Communication Engineering     Open Access   (Followers: 8)
Emerging and Selected Topics in Circuits and Systems     Hybrid Journal   (Followers: 5)
EURASIP Journal on Advances in Signal Processing     Open Access   (Followers: 7)
Ferroelectrics     Hybrid Journal   (Followers: 2)
Ferroelectrics Letters Section     Hybrid Journal   (Followers: 1)
Frequenz     Hybrid Journal   (Followers: 3)
Frontiers of Electrical and Electronic Engineering     Hybrid Journal   (Followers: 6)
IEA Electricity Information     Full-text available via subscription   (Followers: 6)
IEEE Access     Open Access   (Followers: 6)
IEEE Electrical Insulation Magazine     Full-text available via subscription   (Followers: 9)
IEEE Signal Processing Magazine     Full-text available via subscription   (Followers: 36)
IEEE Transactions on Control of Network Systems     Hybrid Journal  
IEEE Transactions on Dielectrics and Electrical Insulation     Hybrid Journal   (Followers: 5)
IEEJ Transactions on Electrical and Electronic Engineering     Hybrid Journal   (Followers: 9)
IET Control Theory & Applications     Hybrid Journal   (Followers: 12)
IET Electric Power Applications     Hybrid Journal   (Followers: 10)
IET Electrical Systems in Transportation     Hybrid Journal   (Followers: 7)
IETE Journal of Education     Open Access   (Followers: 2)
Ingeniería Electrónica, Automática y Comunicaciones     Open Access  
Integrated Ferroelectrics: An International Journal     Hybrid Journal   (Followers: 1)
International Journal of Advanced Electronics and Communication Systems     Open Access   (Followers: 5)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 3)
International Journal of Electrical and Computer Engineering     Open Access   (Followers: 10)
International Journal of Electrical Engineering Education     Full-text available via subscription   (Followers: 6)
International Journal of Electrical Power & Energy Systems     Open Access   (Followers: 11)
International Journal of Emerging Electric Power Systems     Hybrid Journal   (Followers: 5)
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: 4)
International Journal on Communication     Full-text available via subscription   (Followers: 11)
International Journal on Control System and Instrumentation     Full-text available via subscription   (Followers: 11)
International Journal on Electrical and Power Engineering     Full-text available via subscription   (Followers: 10)
International Journal on Signal and Image Processing     Full-text available via subscription   (Followers: 3)
International Transaction of Electrical and Computer Engineers System     Open Access  
International Transactions on Electrical Energy Systems     Hybrid Journal   (Followers: 7)
J3eA     Open Access   (Followers: 2)
Journal of Control, Automation and Electrical Systems     Hybrid Journal   (Followers: 5)
Journal of Electrical and Computer Engineering     Open Access   (Followers: 7)
Journal of Electrical and Computer Engineering Innovations     Open Access   (Followers: 2)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 4)
Journal of Electrical Bioimpedance     Full-text available via subscription   (Followers: 2)
Journal of Electrical Engineering     Open Access   (Followers: 9)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 2)
Journal of Electrical Systems and Information Technology     Open Access  
Journal of Field Robotics     Hybrid Journal   (Followers: 3)
Journal of Micro-Bio Robotics     Hybrid Journal   (Followers: 1)
Journal of Microwaves, Optoelectronics and Electromagnetic Applications     Open Access   (Followers: 7)
Journal of Power Technologies     Open Access   (Followers: 2)
Journal of the Society for Information Display     Hybrid Journal   (Followers: 1)
Journal of Zhejiang University SCIENCE C     Hybrid Journal  
Jurnal Infotel     Open Access  
Jurnal Nasional Teknik Elektro     Open Access   (Followers: 1)
Jurnal Rekayasa Elektrika     Open Access  
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 1)
Majlesi Journal of Electrical Engineering     Open Access  
Micro and Nano Systems Letters     Open Access   (Followers: 4)
Nanotechnology Development     Open Access   (Followers: 4)
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: 7)
Recent Patents on Electrical & Electronic Engineering     Full-text available via subscription   (Followers: 2)
Recent Patents on Telecommunications     Full-text available via subscription   (Followers: 1)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 1)
Russian Electrical Engineering     Hybrid Journal   (Followers: 4)
Scientific Journal of Electrical Engineering     Open Access   (Followers: 5)
SID Symposium Digest of Technical Papers     Hybrid Journal   (Followers: 1)
Sustainable Energy, Grids and Networks     Hybrid Journal  
Sustainable Energy, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Synthesis Lectures on Electrical Engineering     Full-text available via subscription   (Followers: 1)
Telematique     Open Access  
TELKOMNIKA : Indonesian Journal of Electrical Engineering     Open Access   (Followers: 9)
Trends in Electrical Engineering     Full-text available via subscription   (Followers: 2)
Turkish Journal of Electrical Engineering and Computer Science     Open Access   (Followers: 1)
Universal Journal of Electrical and Electronic Engineering     Open Access  
Wireless Engineering and Technology     Open Access   (Followers: 2)
Електротехніка і Електромеханіка     Open Access  
Journal Cover   Sustainable Energy, IEEE Transactions on
  [SJR: 2.826]   [H-I: 24]   [8 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1949-3029
   Published by Institute of Electrical and Electronics Engineers (IEEE) Homepage  [176 journals]
  • IEEE Transactions on Sustainable Energy society information
    • Abstract: Provides a listing of board members, committee members and society officers.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • IEEE Power Engineering Society information for authors
    • Abstract: These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Table of Contents
    • Pages: 1182
      Abstract: Presents the table of contents for this issue of the publication.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • IEEE Transactions on Sustainable Energy
    • Abstract: Provides a listing of the editors, board members, and current staff for this issue of the publication.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Analysis of a Wave Front Parallel WEC Prototype
    • Authors: Sproul; A.;Weise, N.;
      Pages: 1183 - 1189
      Abstract: Nowadays, clean renewable energy extraction solutions are becoming a crucial practice in society. Many different sources are being developed including ocean energy and in specific, ocean waves. In deep water conditions, ocean waves can become very power dense, continuous, and forecastable. Wave height, velocity, and frequency are all variable wave characteristics making it challenging to capture wave power economically. The RTI F2 is a promising wave energy conversion device that is currently under research. Its method of power capture is a buoyant vessel oriented normal to oncoming waves. This paper discusses known control methods implemented on the RTI F2, the experimental setup used for control of the device, and wave tank testing done at the University of New Hampshire's Chase Laboratory. Experimental data was obtained across various wave conditions, plate angles, vessel weights, and control strategies. The results of these tests are presented in the subject matter.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Sensorless Battery Internal Temperature Estimation Using a Kalman Filter
           With Impedance Measurement
    • Authors: Richardson; R.R.;Howey, D.A.;
      Pages: 1190 - 1199
      Abstract: This study presents a method of estimating battery- cell core and surface temperature using a thermal model coupled with electrical impedance measurement, rather than using direct surface temperature measurements. This is advantageous over previous methods of estimating temperature from impedance, which only estimate the average internal temperature. The performance of the method is demonstrated experimentally on a 2.3-Ah lithium-ion iron phosphate cell fitted with surface and core thermocouples for validation. An extended Kalman filter (EKF), consisting of a reduced-order thermal model coupled with current, voltage, and impedance measurements, is shown to accurately predict core and surface temperatures for a current excitation profile based on a vehicle drive cycle. A dual-extended Kalman filter (DEKF) based on the same thermal model and impedance measurement input is capable of estimating the convection coefficient at the cell surface when the latter is unknown. The performance of the DEKF using impedance as the measurement input is comparable to an equivalent dual Kalman filter (DKF) using a conventional surface temperature sensor as measurement input.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Online Fault Detection in PV Systems
    • Authors: Platon; R.;Martel, J.;Woodruff, N.;Chau, T.Y.;
      Pages: 1200 - 1207
      Abstract: This paper presents the development of a practical fault detection approach in photovoltaic (PV) systems, intended for online implementation. The approach was developed and validated using field measurements from a Canadian PV system. It has a fairly low degree of complexity, but achieves a high fault detection rate and is able to successfully cope with abnormalities present in real-life measurements. The fault detection is based on the comparison between the measured and model prediction results of the ac power production. The model estimates the ac power production using solar irradiance and PV panel temperature measurements. Prior to model development, a data analysis procedure was used to identify values not representative of a normal PV system operation. The original 10-min measurements were averaged over 1h, and both datasets were used for modeling. In order to better represent the PV system performance at different sunlight levels, models for different irradiance ranges were developed. The results reveal that the models based on hourly averages are more accurate than the models using 10-min measurements, and the models for different irradiance intervals lead to a fault detection rate greater than 90%. The PV system performance ratio (PR) was used to keep track of the system's long-term performance.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Expanding Existing Solar Irradiance Monitoring Network Using Entropy
    • Authors: Dazhi Yang;Nan Chen;
      Pages: 1208 - 1215
      Abstract: Many existing solar irradiance monitoring networks were built particularly for resource assessment purposes; they are often spatially sparse. In order for the networks to handle other increasingly important tasks, such as irradiance forecasting for grid integration, their spatial sparsity must be addressed by adding in new monitoring stations. Optimally expanding these networks using historical information thus becomes an important research topic for engineers. Variability of solar irradiance in space and time can be quantified using statistics such as entropy and covariance. The deployment of the additional monitoring stations should, therefore, utilize these statistics to reduce the variability. More specifically, we aim at maximizing the entropy of the network. A practical difficulty in statistical modeling of solar irradiance is that the data are not ideal. Properties such as stationarity and isotropy are not observed in irradiance random field. We, therefore, focus on hypothesis testing and transformation of the irradiance data, so that the design procedure is statistically justified. We propose the redesign framework in a solar engineering context, using data from 24 irradiance monitoring stations on a tropical island. In the case study, we demonstrate how to find three optimal stations from a pool of 100 potential future monitoring sites.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Multistep Wind Power Forecast Using Mean Trend Detector and Mathematical
           Morphology-Based Local Predictor
    • Authors: Wu; J.L.;Ji, T.Y.;Li, M.S.;Wu, P.Z.;Wu, Q.H.;
      Pages: 1216 - 1223
      Abstract: This paper proposes a novel forecasting model based on a mean trend detector (MTD) and a mathematical morphologybased local predictor (MMLP) to undertake short-term forecast of wind power generation. In the proposed MTD/MMLP model, the nonstationary time series describing wind power generation is first decomposed by the MTD, which employs some new notions and conventional morphological operators. The decomposition yields two components-the mean trend, which reveals the tendency of the time series, and the stochastic component, which depicts the fluctuations caused by high frequency of the variability. Subsequently, the p-step forecast is conducted for these two components separately. The mean trend is forecasted on the basis of the least-square support vector machine (LS-SVM) model, while the p-step forecast for the stochastic component is carried out by the MMLP, which involves performing morphological operations employing a novel structuring element (SE) in the phase space. Finally, the forecast of wind power generation is achieved by combining the separate forecasts of two components. In order to evaluate the accuracy and stability of the MTD/MMLP model, simulation studies are carried out using the data obtained from three widely used databases sampled in different periods. The results demonstrate that the MTD/MMLP model provides a more accurate and stable forecast compared to the traditional methods.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Incorporating PV Inverter Control Schemes for Planning Active Distribution
    • Authors: AlKaabi; S.S.;Khadkikar, V.;Zeineldin, H.H.;
      Pages: 1224 - 1233
      Abstract: The distribution network planning under active network management (ANM) schemes is becoming of interest due to substantial benefits in facilitating the increasing integration of renewable energy sources. This paper presents various potential ANM schemes based on the photovoltaic inverter control (PVIC) considering enhanced utilization of the inverter reactive power capability. Depending on the active power generation of PV arrays, inverter size and desired reactive power settings, several PVIC schemes are proposed. The PVIC schemes are incorporated in the optimal power flow (OPF) and formulated as a nonlinear programming (NLP) problem. In this study, the PVIC schemes are applied to maximize the total wind-distributed generation (DG) penetration on a typical U.K. distribution system. Various case studies are presented and compared to evaluate the performance. The results show that the proposed schemes can significantly increase the wind penetration levels by 45.4% and up to 92.3%.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Integrated Modeling and Assessment of the Operational Impact of
           Power-to-Gas (P2G) on Electrical and Gas Transmission Networks
    • Authors: Clegg; S.;Mancarella, P.;
      Pages: 1234 - 1244
      Abstract: Power-to-gas (P2G) is the process whereby electricity is used to produce hydrogen or synthetic natural gas. The electricity for the P2G process could, for instance, come from renewable energy which would otherwise be curtailed due to system or line constraints. The existing natural gas network could then potentially be used as a means to store, transport, and reutilize this energy, thus preventing its waste. While there are several ongoing discussions on P2G in different countries, these are generally not backed by quantitative studies on its potential network implications and benefits. To bridge this gap, this paper introduces an original methodology to analyze different P2G processes and assess their operational impacts on both electricity and gas transmission networks. This is carried out by using a novel integrated model specifically developed for the simulation of operational interdependences between the two networks considering P2G. To demonstrate the several innovative features of the proposed model, technical, environmental, and economic operational aspects of P2G and its potential benefits are analyzed on the case of the Great Britains system, also providing insights into relief of gas and electrical transmission network constraints.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Modeling and Health Monitoring of DC Side of Photovoltaic Array
    • Authors: Akram; M.N.;Lotfifard, S.;
      Pages: 1245 - 1253
      Abstract: In this paper, a health monitoring method for photovoltaic (PV) systems based on probabilistic neural network (PNN) is proposed that detects and classifies short- and open-circuit faults in real time. To implement and validate the proposed method in computer programs, a new approach for modeling PV systems is proposed that only requires information from manufacturers datasheet reported under normal-operating cell temperature (NOCT) conditions and standard-operating test conditions (STCs). The proposed model precisely represents characteristics of PV systems at different temperatures, as the temperature dependency of parameters such as ideality factor, series resistance, and thermal voltage is considered in the proposed model. Although this model can be applied to a variety of applications, it is specifically used to test and validate the performance of the proposed fault detection and classification method.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Fast Unscented Transformation-Based Transient Stability Margin Estimation
           Incorporating Uncertainty of Wind Generation
    • Authors: KeQian Hua;Mishra; Y.;Ledwich, G.;
      Pages: 1254 - 1262
      Abstract: Intermittent generation from wind farms leads to fluctuating power system operating conditions pushing the stability margin to its limits. The traditional way of determining the worst case generation dispatch for a system with several semi-scheduled wind generators yields a conservative solution. This paper proposes a fast estimation of the transient stability margin (TSM) incorporating the uncertainty of wind generation. First, the Kalman filter (KF) is used to provide linear estimation of system angle and then unscented transformation (UT) is used to estimate the distribution of the TSM. The proposed method is compared with the traditional Monte Carlo (MC) method and the effectiveness of the proposed approach is verified using Single Machine Infinite Bus (SMIB) and IEEE 14 generator Australian dynamic system. This method will aid grid operators to perform fast online calculations to estimate TSM distribution of a power system with high levels of intermittent wind generation.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Probabilistic-Based Available Transfer Capability Assessment Considering
           Existing and Future Wind Generation Resources
    • Authors: Pengwei Du;Weifeng Li;Xinda Ke;Ning Lu;Ciniglio; O.A.;Colburn, M.;Anderson, P.M.;
      Pages: 1263 - 1271
      Abstract: This paper presents a probabilistic-based approach for available transfer capability (ATC) assessment. A composite algorithm is developed to generate ensembles of future wind generation scenarios for the existing and planned wind sites using both measured and model-produced wind data. Then, the ensembles of wind and load are used to calculate their respective probability density functions (pdfs), which are subsequently used to calculate the probabilistic-based ATC for a selected transmission corridor. The method has been tested and validated using historical and operational data provided by the Idaho Power Co. The results show that the method can effectively quantify the uncertainties in the ATC assessment introduced by variable generation resources and load variations. As a result, the grid planners will inform the likelihood for the transmission corridor to exceed its transfer capacity in any targeted future years as well as the duration of such events.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Optimized Placement of Wind Turbines in Large-Scale Offshore Wind Farm
           Using Particle Swarm Optimization Algorithm
    • Authors: Peng Hou;Weihao Hu;Soltani; M.;Zhe Chen;
      Pages: 1272 - 1282
      Abstract: With the increasing size of wind farms, the impact of the wake effect on wind farm energy yields become more and more evident. The arrangement of locations of the wind turbines (WTs) will influence the capital investment and contribute to the wake losses, which incur the reduction of energy production. As a consequence, the optimized placement of the WTs may be done by considering the wake effect as well as the components cost within the wind farm. In this paper, a mathematical model which includes the variation of both wind direction and wake deficit is proposed. The problem is formulated by using levelized production cost (LPC) as the objective function. The optimization procedure is performed by a particle swarm optimization (PSO) algorithm with the purpose of maximizing the energy yields while minimizing the total investment. The simulation results indicate that the proposed method is effective to find the optimized layout, which minimizes the LPC. The optimization procedure is applicable for optimized placement of WTs within wind farms and extendible for different wind conditions and capacity of wind farms.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • A Short-Term Wind Power Forecasting Approach With Adjustment of Numerical
           Weather Prediction Input by Data Mining
    • Authors: Qianyao Xu;Dawei He;Ning Zhang;Chongqing Kang;Qing Xia;Jianhua Bai;Junhui Huang;
      Pages: 1283 - 1291
      Abstract: This paper proposes a novel short-term wind power forecasting approach by mining the bad data of numerical weather prediction (NWP). Today's short-term wind power forecast (WPF) highly depends on the NWP, which contributes the most in the WPF error. This paper first introduces a bad data analyzer to fully study the relationship between the WPF error with several new extracted features from the raw NWP. Second, a hierarchical structure is proposed, which is composed of a K-means clustering-based bad data detection module and a neural network (NN)-based forecasting module. In the NN module, the WPF is fully adjusted based on the output of the bad data analyzer. Simulations are performed comparing with two other different methods. It proves that the proposed approach can improve the short-term wind power forecasting by effectively identifying and adjusting the errors from NWP.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Reduced-Order Small-Signal Model of Microgrid Systems
    • Authors: Rasheduzzaman; M.;Mueller, J.A.;Kimball, J.W.;
      Pages: 1292 - 1305
      Abstract: The objective of this study was to develop a reduce-dorder small-signal model of a microgrid system capable of operating in both the grid-tied and the islanded conditions. The nonlinear equations of the proposed system were derived in the dq reference frame and then linearized around stable operating points to construct a small-signal model. The high-order state matrix was then reduced using the singular perturbation technique. The dynamic equations were divided into two groups based on the small-signal model parameters ε. The “slow” states, which dominated the system's dynamics, were preserved, whereas the “fast” states were eliminated. Step responses of the model were compared to the experimental results from a hardware test to assess their accuracy and similarity to the full-order system. The proposed reduced-order model was applied to a modified IEEE-37 bus grid-tied microgrid system to evaluate system's dynamic response in grid-tied mode, islanded mode, and transition from grid-tied to islanded mode.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Multiobjective Optimization Dispatch for Microgrids With a High
           Penetration of Renewable Generation
    • Authors: Ross; M.;Abbey, C.;Bouffard, F.;Joos, G.;
      Pages: 1306 - 1314
      Abstract: Many benefits can be achieved through the implementation of a Microgrid controller, such as minimized cost, reduction in peak power, power smoothing, greenhouse gas emission reduction, and increased reliability of service. However, most Microgrid controllers found in the literature and in the industry optimize a single objective, which either exacerbates or does not solve the problems with integrating a high penetration of renewable energy. This paper presents a methodology of formulating a multiobjective optimization (MOO) so that each objective is quantified through valuation functions that can be specific to every Microgrid. The proposed approach attains a Pareto-optimal solution by directly comparing the quantified valuation functions and solving as if it were a single-objective optimization (SOO) problem. Three cases of controllers are presented and compared: 1)a base case system with no controller; 2)an SOO that optimizes the cost of energy; and 3)an MOO that optimizes five identified benefits. Results show that the proposed controller can mitigate the negative impacts of volatile generation to levels below that of the system load.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Stochastic Distribution System Operation Considering Voltage Regulation
           Risks in the Presence of PV Generation
    • Authors: Agalgaonkar; Y.P.;Pal, B.C.;Jabr, R.A.;
      Pages: 1315 - 1324
      Abstract: Variable over voltage, excessive tap counts, and voltage regulator (VR) runaway condition are major operational challenges in distribution network while accommodating generation from photovoltaics (PVs). The conventional approach to achieve voltage control based on offline simulation for voltage set point calculation does not consider forecast errors. In this work, a stochastic optimal voltage control strategy is proposed while considering load and irradiance forecast errors. Stochastic operational risks such as overvoltage and VR runaway are defined through a chance constrained optimization (CCO) problem. This classical formulation to mitigate runaway is further improved by introducing a stochastic index called the Tap Tail Expectation. Operational objectives such as power losses and excessive tap count minimization are considered in the formulation. A sampling approach is proposed to solve the CCO. Along with other voltage control devices, the PV inverter voltage support features are coordinated. The simulation study is performed using a realistic distribution system model and practically measured irradiance to demonstrate the effectiveness of the proposed technique. The proposed approach is a useful operational procedure for distribution system operators. The approach can minimize feeder power losses, avoid voltage violations, and alleviate VR runaway.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Modeling of Grid-Connected DFIG-Based Wind Turbines for DC-Link Voltage
           Stability Analysis
    • Authors: Jiabing Hu;Yunhui Huang;Dong Wang;Hao Yuan;Xiaoming Yuan;
      Pages: 1325 - 1336
      Abstract: The electromagnetic stability issues of the grid-connected doubly fed induction generator (DFIG) system are usually overlooked. This paper presents a reduced order small-signal model that can be used to analyze the stability of DFIGs dc-link voltage control system, especially under weak ac grid conditions. This model neglects DFIG flux and fast current control dynamics. However, the effects of operating points, grid strengths and control loops interactions on system dynamic performance are taken into account. An eigenvalue comparison shows the proposed model holds dominant oscillation mode featured by the detailed model and is suitable for stability analysis of dc-link voltage control system of DFIG. Influence coefficients reflecting control loops interactions are also presented. Application studies of the proposed model show it is suitable for illustrating the effect of grid strength on dynamic performance of the DFIGs dc-link voltage control system. Meanwhile, phase-locked loop (PLL) and rotor-side converter (RSC) active power control (APC)/reactive power controls (RPC) effect on system stability are also explored.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • A Versatile Probability Model of Photovoltaic Generation Using Pair Copula
    • Authors: Wei Wu;Keyou Wang;Bei Han;Guojie Li;Xiuchen Jiang;Crow; M.L.;
      Pages: 1337 - 1345
      Abstract: Photovoltaic (PV) generation is increasingly popular in power systems. The nonlinear dependence associated with a large number of distributed PV sources adds the complexity to construct an accurate probability model and negatively affects confidence levels and reliability, thereby resulting in a more challenging operation of the systems. Most probability models have many restrictions when constructing multiple PV sources with complex dependence. This paper proposes a versatile probability model of PV generation on the basis of pair copula construction. In order to tackle the computational burden required to construct pair copula in high-dimensional cases, a systematic simplification technique is utilized that can significantly reduce the computational effort while preserving satisfactory precision. The proposed method can simplify the modeling procedure and provide a flexible and optimal probability model for the PV generation with complex dependence. The proposed model is tested using a set of historical data from colocated PV sites. It is then applied to the probabilistic load flow (PLF) study of the IEEE 118-bus system. The results demonstrate the effectiveness and accuracy of the proposed model.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • MF-APSO-Based Multiobjective Optimization for PV System Reactive Power
    • Authors: Hong-Tzer Yang;Jian-Tang Liao;
      Pages: 1346 - 1355
      Abstract: This paper proposes a reactive power-regulation strategy for a distribution system connected with high-penetration photovoltaic (PV) generation. The PV reactive power regulation is formulated as a multiobjective optimization problem to relieve the overvoltage caused by high PV penetration and to minimize total line loss. With integrated power-flow analysis, a new mutation fuzzy adaptive particle swarm optimization (MF-APSO) algorithm is proposed to solve the multiobjective optimization problem. The proposed reactive power-regulation strategy and MF-APSO algorithm are, respectively, compared with conventional methods for overvoltage mitigation and total line-loss reduction, as well as with the referenced optimization algorithms for the problems of concern. Numerical results verify that the proposed multiobjective optimization method can more effectively mitigate the overvoltage issue and greatly reduce the total line loss as compared to other methods. Utilization of high-penetration PV systems can thus be further enhanced with reduced power curtailment owing to the added functions of voltage regulation and line-loss minimization.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Optimal Wind Reversible Hydro Offering Strategies for Midterm Planning
    • Authors: Sanchez de la Nieta; A.A.;Contreras, J.;Munoz, J.I.;Catalao, J.P.S.;
      Pages: 1356 - 1366
      Abstract: A coordinated strategy between wind and reversible hydro units for the midterm planning that reduces the imbalance of wind power and improves system efficiency is proposed. A stochastic mixed integer linear model is used, which maximizes the joint profit of wind and hydro units, where conditional value at risk (CVaR) is used for model risk. The offering strategies studied are 1)separate wind and hydro pumping offer, where the units work separately without a physical connection and 2)a single wind and hydro pumping offer with a physical connection between them to store wind energy for future use. The effects of a coordinated wind-hydro strategy for midterm planning are analyzed, considering CVaR and the future water value. The future water value in the reservoirs is analyzed hourly for a period of 1 week and 2 months, in two realistic case studies.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Demand Response for Residential Electric Vehicles With Random Usage
           Patterns in Smart Grids
    • Authors: Rassaei; F.;Wee-Seng Soh;Kee-Chaing Chua;
      Pages: 1367 - 1376
      Abstract: Electric vehicles (EVs) are expected to become widespread in future years. Thus, it is foreseen that EVs will become the new high-electricity-consuming appliances in the households. The characteristics of the extra power load that they impose on the distribution grid follow the patterns of people's random usage behaviors. In this paper, we seek to provide answers to the following question: assigning real-world randomness to the EVs' availability in the households and their charging requirements, how can EVs' demand response (DR) help to minimize the peak power demand and, in general, shape the aggregated demand profile of the system? We present a general demand-shaping problem applicable for limit order bids to a day-ahead (DA) energy market. We propose an algorithm for distributed DR of the EVs to shape the daily demand profile or to minimize the peak demand. Additionally, we put these problems in a game framework. Extensive simulations show that, for certain practical distributions of EVs' usage, it is possible to accommodate EVs for all the users in the system and yet achieve the same peak demand as when there is no EV in the system without any changes in the users' commuting behaviors.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Decentralized Multiarea Robust Generation Unit and Tie-Line Scheduling
           Under Wind Power Uncertainty
    • Authors: Zhigang Li;Shahidehpour; M.;Wenchuan Wu;Bo Zeng;Boming Zhang;Weiye Zheng;
      Pages: 1377 - 1388
      Abstract: The growing interconnections of regional power systems and the large-scale integration of wind energy bring about the critical need to coordinate multiarea generation unit and tie-line scheduling (MAUTS). It is recognized that because of the limitations on private data exchange and model management, it is suitable to address the multiarea power scheduling problem in a decentralized way. In this paper, the MAUTS problem is formulated using the adaptive robust optimization (RO) scheme to account for uncertain wind energy. Our model is decomposed into regional subproblems by augmented Lagrangian decomposition (ALD), which enables a fully distributed computation within an alternating direction multiplier method framework. To address the nonconvexity issue, a tractable alternating optimization procedure (AOP) is developed to obtain high-quality solutions with finite convergence for the nonconvex mixed-integer problem. Simulations on different test systems are conducted to show the computational performance, the solution quality, and scalability of the proposed method.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Real-Time HIL Implementation of Sliding Mode Control for Standalone System
           Based on PV Array Without Using Dumpload
    • Authors: Rezkallah; M.;Hamadi, A.;Chandra, A.;Singh, B.;
      Pages: 1389 - 1398
      Abstract: In this paper, hardware-in-the-loop (HIL) implementation of solar photovoltaic (PV) array feeding autonomous load, without dump load, is investigated. Two control algorithms based on the sliding mode approach are designed to guarantee a fast and finite-time convergence without adjustment of the system parameters. The dc-dc boost converter and the current controlled-voltage source converter (CC-VSC) are controlled to maximize the power from the PV, to protect the battery energy storage system (BESS) from overcharging, and to regulate the voltage and frequency at the point of common coupling (PCC). An accurate stability analysis of the system is presented and discussed in this work. The effectiveness and the robustness of the developed controllers are validated by simulation and experimental results during the load perturbation and varying climate conditions.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Identification of Unavoidable Branch Limit Violations Due to Wind Forecast
    • Authors: Xiaoguang Li;Tate; J.E.;
      Pages: 1399 - 1408
      Abstract: One role of grid operators is to identify potential problems before they occur and, if necessary, take preemptive actions. As wind generation becomes increasingly widespread, there is the potential for credible, simultaneous fluctuations of output at different locations to result in limit violations. Existing analysis methods that consider forecast errors either inadequately model the control responses available to system operators (e.g., using participation factors) or ignore network constraints, which limits their utility in identifying situations that would require operator action. An alternative method of handling forecast errors, utilizing bilevel programming, is proposed here to identify situations that may result in branch overloads. What distinguishes this method from prior approaches is that it only identifies overloads that can occur despite optimal operator reaction to forecast errors--i.e., when the overload is unavoidable, given current control capabilities. Studies conducted on 37- and 118-bus test systems demonstrate both the utility and feasibility of using this method for online operations.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Piezoelectric Energy Harvester With Shape Memory Alloy Actuator Using
           Solar Energy
    • Authors: Reddy; A.R.;Umapathy, M.;Ezhilarasi, D.;Uma, G.;
      Pages: 1409 - 1415
      Abstract: A piezoelectric cantilever beam-based energy harvester working with solar energy is proposed in this paper. The piezoelectric cantilever beam is excited by a shape memory alloy (SMA) spring actuator. The heating and cooling of the SMA actuator is done by designing an appropriate piping and transport system with water as a working fluid. The frequency and amplitude of excitation force exerted by an SMA actuator to the piezoelectric cantilever beam depend on the flow rate of water used for heating and cooling of SMA and the temperature of the water. The energy harvester is modeled analytically and fabricated to evaluate its performance in the laboratory. The analytical and experimental results show that higher output voltage from the energy harvester can be obtained with higher water temperature and frequency of the output voltage is limited to the dynamics of the SMA actuator. The voltage generated with the proposed energy harvester at the flow rate of 24 ml/s with the temperature of 70 °C is found to be 12 V. The harvester utilizes only the solar energy for its operation and hence the proposed design is a new addition to the area of energy harvesting using piezoelectric cantilever beam.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Predictive Deep Boltzmann Machine for Multiperiod Wind Speed Forecasting
    • Authors: Chun-Yang Zhang;Chen; C.L.P.;Min Gan;Long Chen;
      Pages: 1416 - 1425
      Abstract: It is important to forecast the wind speed for managing operations in wind power plants. However, wind speed prediction is extremely complex and difficult due to the volatility and deviation of the wind. As existing forecasting methods directly model the raw wind speed data, it is difficult for them to provide higher inference accuracy. Differently, this paper presents a sophisticated deep-learning technique for short-term and long-term wind speed forecast, i.e., the predictive deep Boltzmann machine (PDBM) and corresponding learning algorithm. The proposed deep model forecasts wind speed by analyzing the higher level features abstracted from lower level features of the wind speed data. These automatically learnt features are very informative and appropriate for the prediction. The proposed PDBM is a deep stochastic model that can represent the wind speed very well, and is inspired by two aspects. 1) The stochastic model is suitable to capture the probabilistic characteristics of wind speed. 2) Recent developments in neural networks with deep architectures show that deep generative models have competitive capability to approximate nonlinear and nonsmooth functions. The evaluation of the proposed PDBM model is depicted by both hour-ahead and day-ahead prediction experiments based on real wind speed datasets. The prediction accuracy of the PDBM model outperforms existing methods by more than 10%.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • A New Sensorless Hybrid MPPT Algorithm Based on Fractional Short-Circuit
           Current Measurement and P&O MPPT
    • Authors: Sher; H.A.;Murtaza, A.F.;Noman, A.;Addoweesh, K.E.;Al-Haddad, K.;Chiaberge, M.;
      Pages: 1426 - 1434
      Abstract: This paper presents a new maximum power point tracking (MPPT) method for photovoltaic (PV) systems. The proposed method improves the working of the conventional perturb and observe (P&O) method in changing environmental conditions by using the fractional short-circuit current (FSCC) method. It takes the initial operating point of a PV system by using the short-circuit current method and later shifts to the conventional P&O technique. The advantage of having this two-stage algorithm is rapid tracking under changing environmental conditions. In addition, this scheme offers low-power oscillations around MPP and, therefore, more power harvesting compared with the common P&O method. The proposed MPPT decides intelligently about the moment of measuring short-circuit current and is, therefore, an irradiance sensorless scheme. The proposed method is validated with computer software simulation followed by a dSPACE DS1104-based experimental setup. A buck-boost dc-dc converter is used for simulation and experimental confirmation. Furthermore, the reliability of the proposed method is also calculated. The results show that the proposed MPPT technique works satisfactorily under given environmental scenarios.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Optimum Shunt Capacitor Placement in Multimicrogrid Systems With
           Consideration of Islanded Mode of Operation
    • Authors: Farag; H.E.Z.;El-Saadany, E.F.;
      Pages: 1435 - 1446
      Abstract: Appropriate implementation of multimicrogrid systems in distribution networks is dependent on the development of new planning methodologies that take into account the special operational characteristics of microgrids. This paper proposes a new algorithm for optimum shunt capacitor placement in multimicrogrid systems with consideration of islanded mode of operation. The cost function of the proposed optimization technique consists of three terms in the planning process: 1)the cost of power and energy losses when multimicrogrid systems operate in normal grid-connected mode; 2)the cost of capital investments of the installed shunt capacitors; and 3)the customers cost of interruption when microgrids fail to operate in islanded mode due to shortage of reactive power and/or voltage violations. Appropriate power flow and probabilistic models for distributed and renewable energy resources (DER) and loads have been incorporated in the optimization problem to provide proper representation for microgrids during both grid-connected and islanded modes of operation. A genetic algorithm (GA) has been utilized to solve the problem and several case studies have been conducted to validate the proposed capacitor placement methodology. The results show that the new methodology can facilitate successful deployment of microgrids in distribution networks.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Wind Power Forecasting Using Neural Network Ensembles With Feature
    • Authors: Song Li;Peng Wang;Goel; L.;
      Pages: 1447 - 1456
      Abstract: In this paper, a novel ensemble method consisting of neural networks, wavelet transform, feature selection, and partial least-squares regression (PLSR) is proposed for the generation forecasting of a wind farm. Based on the conditional mutual information, a feature selection technique is developed to choose a compact set of input features for the forecasting model. In order to overcome the nonstationarity of wind power series and improve the forecasting accuracy, a new wavelet-based ensemble scheme is integrated into the model. The individual forecasters are featured with different mixtures of the mother wavelet and the number of decomposition levels. The individual outputs are combined to form the ensemble forecast output using the PLSR method. To confirm the effectiveness, the proposed method is examined on real-world datasets and compared with other forecasting methods.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Sizing Energy Storage to Mitigate Wind Power Forecast Error Impacts by
           Signal Processing Techniques
    • Authors: Bitaraf; H.;Rahman, S.;Pipattanasomporn, M.;
      Pages: 1457 - 1465
      Abstract: This paper proposes to use discrete Fourier transform (DFT) and discrete wavelet transform (DWT) methods to schedule grid-scale energy storage systems to mitigate wind power forecast error impacts while considering energy storage properties. This is accomplished by decomposing the wind forecast error signal to different time-varying periodic components to schedule sodium sulfur (NaS) batteries, compressed air energy storage (CAES), and conventional generators. The advantage of signal processing techniques is that the resultant decomposed components are appropriate for cycling of each energy storage technology. It is also beneficial for conventional generators, which are more efficient to operate close to rated capacity. The tradeoff between installing more energy storage units and decreasing the wind spillage, back-up energy, and the standard deviation of residual forecast error signal is analyzed. The NaS battery life cycle analysis and CAES contribution on increasing NaS battery lifetime are studied. The impact of considering the frequency bias constant to allow small frequency deviations is also investigated. To showcase the applicability of the proposed approach, a simulation case study based on a real-world 5-min interval wind data from Bonneville Power Administration (BPA) in 2013 is presented.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • A Stochastic Investment Model for Renewable Generation in Distribution
    • Authors: Montoya-Bueno; S.;Munoz, J.I.;Contreras, J.;
      Pages: 1466 - 1474
      Abstract: A model to obtain the optimal allocation and timing of renewable distributed generation under uncertainty is proposed as part of distribution expansion planning. The problem is formulated using a stochastic two-stage multiperiod mixed-integer linear programming (MILP) model, where investment decisions are done in the first stage and scenario-dependent operation variables are solved in the second stage. The model aims to minimize renewable distributed generation (photovoltaic and wind) investment costs, substation expansion investment cost, operation and maintenance costs, energy losses cost, and the cost of the power purchased from the transmission system. Active and reactive power flow equations are linearized and constraints include voltage limits, substation and feeders capacities, renewable generation limits, and investment constraints. The model is tested on a 34-bus system and conclusions are duly drawn.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Mitigating Voltage Problem in Distribution System With Distributed Solar
           Generation Using Electric Vehicles
    • Authors: Lin Cheng;Yao Chang;Huang; R.;
      Pages: 1475 - 1484
      Abstract: Distributed solar generation has the potential to reach high penetration levels in distribution systems. However, its integration reshapes distribution system power flows and causes rapid-fluctuations in system statuses. The facts challenge major voltage management approaches, nowadays, such as using online load tap changing (OLTC) transformers, voltage regulators (VRs), or shunt capacitors. In this paper, we explore the capability of using vehicle-to-grid (V2G) electric vehicles (EVs) to join distribution system voltage management, and to collaborate with OLTCs to mitigate the voltage problems caused by distribution solar generations. A two-stage control method is proposed for this purpose. The first stage controls the making of rolling schedules for EV charging and OLTC tap positions, while the second controls the EVs to resist the solar generation fluctuation to maintain voltage profiles. A case system with simultaneous overvoltage/undervoltage risks is designed to test the effectiveness of the proposed method. The results demonstrate that both the over/undervoltage risks are mitigated.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • DC Switch Driven Active Power Output Control of Photovoltaic Inverters for
           the Provision of Frequency Regulation
    • Authors: Moutis; P.;Vassilakis, A.;Sampani, A.;Hatziargyriou, N.D.;
      Pages: 1485 - 1493
      Abstract: In this paper, a control strategy for the participation of photovoltaic (PV) systems in frequency regulation is suggested. A number of strings from every inverter of a PV system are kept as reserve by disconnecting them through dc-relays. Hence, as the control algorithm monitors the grid frequency, it reconnects or disconnects strings, according to the occurring frequency deviations (negative and positive, respectively). Contrary to previous approaches, the suggested methodology here avoids the use of storage devices, which implies additional investment costs, and/or the manipulation of the maximum power point tracking (MPPT) algorithm of the inverter, which represents higher control complexity and special considerations depending on each algorithm. Simulation results from frequency phenomena and solar irradiation changes on a two-bus system in MATLAB Simulink are presented to show the favorable behavior and effective performance of the proposed control strategy. The design concept is also experimentally tested under various operating conditions and on different devices; the results also confirm the feasibility and simplicity of the method.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Risk-Averse Preventive Voltage Control of AC/DC Power Systems Including
           Wind Power Generation
    • Authors: Rabiee; A.;Soroudi, A.;Keane, A.;
      Pages: 1494 - 1505
      Abstract: Preventive voltage control (PVC) deals with the alert state of power systems, where the system operates in a stable regime but loading margin (LM) is insufficient or some operational constraints have been violated. Hence, the aim of PVC is to ensure a desired LM (i.e., restoration of normal operation state), while minimizing the corresponding control costs. This paper proposes a new stochastic PVC (SPVC) model for power systems operation, taking into account the uncertainties of wind power generation. The uncertainty of wind power generation is handled using a scenario-based modeling approach. The risk associated with each objective function (OF) is handled using conditional value at risk (CVaR). Voltage set-points of generation units, active power readjustment of predetermined generating units, load reduction of a predetermined load buses, along with the intermittent wind power generation, are employed as control measures in the proposed SPVC approach. Line-commutated converter high-voltage dc (LCC-HVDC) link constraints and doubly fed induction generators (DFIGs) capability curves are also considered in the proposed SPVC approach. To illustrate the effectiveness of the proposed approach, it is applied on the IEEE 39-bus test system. The obtained results substantiate the applicability of the proposed SPVC model to ensure secure operation of ac/dc power systems with high penetration of offshore wind farms.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Decentralized Resource Allocation and Load Scheduling for Multicommodity
           Smart Energy Systems
    • Authors: Blaauwbroek; N.;Nguyen, P.H.;Konsman, M.J.;Huaizhou Shi;Kamphuis, R.I.G.;Kling, W.L.;
      Pages: 1506 - 1514
      Abstract: Due to the expected growth in district heating systems in combination with the development of hybrid energy appliances such as heat pumps (HPs) and micro-combined heat and power (CHP) installations, new opportunities arise for the management of multicommodity energy systems, including electricity, heat, and gas. The possibility to convert forms of energy using hybrid energy appliances and exploiting flexibility from local production and consumption can improve the systems' efficiency significantly. This paper extends existing work with a decentralized version of a multicommodity smart energy management system to deal with flexibility and scalability. The system incorporates both heat and electricity, and integrates various types of flexible appliances as well as hybrid energy appliances. To optimally allocate the available resources and its flexibility, the developed multiagent system (MAS) aims to perform optimal supply and demand matching (SDM) of the local resources and flexible appliances, as well as to flatten out the net remaining exchange over time. The proposed method is applied to a test case, where simulation results confirm that the decentralized approach leads to a scalable solution for the management of the multicommodity smart energy system (MC-SES) and performs similar to the centralized approach.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Emulation of an OWC Ocean Energy Plant With PMSG and Irregular Wave Model
    • Authors: Ramirez; D.;Bartolome, J.P.;Martinez, S.;Herrero, L.C.;Blanco, M.;
      Pages: 1515 - 1523
      Abstract: Ocean energy is a promising resource for renewable electricity generation that presents many advantages, such as being more predictable than wind energy, but also some disadvantages such as large and slow amplitude variations in the generated power. This paper presents a hardware-in-the-loop prototype that allows the study of the electric power profile generated by a wave power plant based on the oscillating water column (OWC) principle. In particular, it facilitates the development of new solutions to improve the intermittent profile of the power fed into the grid or the test of the OWC behavior when facing a voltage dip. Also, to obtain a more realistic model behavior, statistical models of real waves have been implemented.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Contingency Assessment and Network Reconfiguration in Distribution Grids
           Including Wind Power and Energy Storage
    • Authors: Meneses de Quevedo; P.;Contreras, J.;Rider, M.J.;Allahdadian, J.;
      Pages: 1524 - 1533
      Abstract: In case of abnormal conditions, distribution systems should be reconfigured to overcome the impacts of outages such as overloads of network components and increased power losses. For this purpose, energy storage systems (ESS) and renewable energy sources (RES) can be applied to improve operating conditions. An optimal contingency assessment model using two-stage stochastic linear programming including wind power generation and a generic ESS is presented. The optimization model is applied to find the best radial topology by determining the best switching sequence to solve contingencies. The proposed model is applied to a 69-node distribution system and the results of all possible contingencies in the network are examined considering three different case studies with several scenarios. In addition, a reconfiguration analysis including all the contingencies is presented for the case studies.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Long-Term Stability Analysis of Power Systems With Wind Power Based on
           Stochastic Differential Equations: Model Development and Foundations
    • Authors: Xiaozhe Wang;Hsiao-Dong Chiang;Jianhui Wang;Hui Liu;Tao Wang;
      Pages: 1534 - 1542
      Abstract: In this paper, the variable wind power is incorporated into the dynamic model for long-term stability analysis. A theory-based method is proposed for power systems with wind power to conduct long-term stability analysis, which is able to provide accurate stability assessments with fast simulation speed. Particularly, the theoretical foundation for the proposed approximation approach is presented. The accuracy and efficiency of the method are illustrated by several numerical examples.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Wind Power Dispatch Margin for Flexible Energy and Reserve Scheduling With
           Increased Wind Generation
    • Authors: Hedayati-Mehdiabadi; M.;Junshan Zhang;Hedman, K.W.;
      Pages: 1543 - 1552
      Abstract: With the significant penetration of wind generation, the variability and uncertainty of wind energy poses new challenges to power system operations. In particular, more rapid reserve is required, which may result in the scarcity of balancing services. With the increasing penetration of renewable generation, it is envisaged that renewable resources will be required to partake in the system balancing tasks. In this paper, a combined flexible dispatch and reserve scheduling policy is proposed by determining a flexible wind dispatch margin. In order to provide a flexible dispatch margin, wind generators underschedule in the hour-ahead energy market, so as to hold some expected output for reserves. Additional wind energy is then available for mitigating forecast errors and other system uncertainties. This paper presents a framework to find the optimal policy to incorporate the flexible wind dispatch margin into the hour-ahead market. A finite-state Markov chain wind power forecast model, based on spatio-temporal analysis, is utilized. The presented framework is used to find the appropriate level of wind dispatch margin. The proposed approach is tested and the wind generation data are used to analyze the effectiveness of the presented model in coping with forecast errors and achieving a more secure system operation.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Operating Modes and Control Strategy for Megawatt-Scale Hydro-Viscous
           Transmission-Based Continuously Variable Speed Wind Turbines
    • Authors: Xiu-Xing Yin;Yong-Gang Lin;Wei Li;
      Pages: 1553 - 1564
      Abstract: A megawatt (MW)-scale hydro-viscous transmission-based continuously variable speed wind turbine is proposed to guarantee a smooth transition among different operating regions and hence to improve power efficiency and quality. This turbine is achieved by highly integrating a hydro-viscous element into the turbine drive-train to mitigate the upstream wind-loading fluctuations. This element allows the turbine speed to be directly regulated by continuously changing the oil film thickness in this element. Three important operating modes of this turbine system are proposed. The control-oriented drive-train model is also established and validated based on experimental data. A cooperative control strategy over the full operating range is then proposed based on such modes. A series of comparative cosimulations are carried out to evaluate the stability and effectiveness of the proposed turbine system in speed and power regulations. This proposed system holds several advantages such as large power capacity, high efficiency, downsized power converters, and low cost. Such advantages make this turbine system particularly attractive and promising for medium-to-large-scale wind power applications.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Probabilistic Impact of Transportation Electrification on the Loss-of-Life
           of Distribution Transformers in the Presence of Rooftop Solar Photovoltaic
    • Authors: Abdelsamad; S.F.;Morsi, W.G.;Sidhu, T.S.;
      Pages: 1565 - 1573
      Abstract: In this paper, the impact of plug-in electric vehicle (PEV) charging on distribution transformer overload and loss-of-life (LOL) in the presence of rooftop solar photovoltaic (PV) is probabilistically quantified. The Monte Carlo (MC) method is used to address the uncertainties resulting from solar irradiance and temperature in case of solar PV and also to emulate the probabilistic aspect of PEV charging. Twenty scenarios of different penetration levels of solar PVs and PEVs are considered in this work. The results have shown significant reduction in percentage LOL due to solar PV contribution in the case of all-electric (AE) residential dwellings and hence the transformer replacement may be deferred by nearly 4 years, while it has a minor effect in the case of residential dwellings with gas heat and electric water heaters (WWH).
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Endogenous Assessment of the Capacity Value of Solar PV in Generation
           Investment Planning Studies
    • Authors: Munoz; F.D.;Mills, A.D.;
      Pages: 1574 - 1585
      Abstract: There exist several different reliability- and approximation-based methods to determine the contribution of solar resources toward resource adequacy. However, most of these approaches require knowing in advance the installed capacities of both conventional and solar generators. This is a complication since generator capacities are actually decision variables in capacity planning studies. In this paper, we study the effect of time resolution and solar PV penetration using a planning model that accounts for the full distribution of generator outages and solar resource variability. We also describe a modification of a standard deterministic planning model that enforces a resource adequacy target through a reserve margin constraint. Our numerical experiments show that at least 50 days worth of data are necessary to approximate the results of the full-resolution model with a maximum error of 2.5% on costs and capacity. We also show that the amount of displaced capacity of conventional generation decreases rapidly as the penetration of solar PV increases. We find that using an exogenously defined and constant capacity value based on time-series data can yield relatively accurate results for small penetration levels. For higher penetration levels, the modified deterministic planning model better captures avoided costs and the decreasing value of solar PV.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Optimal Design of Solar PV Farms With Storage
    • Authors: Ghiassi-Farrokhfal; Y.;Kazhamiaka, F.;Rosenberg, C.;Keshav, S.;
      Pages: 1586 - 1593
      Abstract: We consider the problem of allocating a capital budget to solar panels and storage to maximize the expected revenue in the context of a large-scale solar farm participating in an energy market. This problem is complex due to many factors. To begin with, solar energy production is stochastic, with a high peak-to-average ratio, thus the access link is typically provisioned at less than peak capacity, leading to the potential waste of energy due to curtailment. The use of storage prevents power curtailment, but the allocation of capital to storage reduces the amount of energy produced. Moreover, energy storage devices are imperfect. A solar farm owner is thus faced with two problems: 1)deciding the level of power commitment and 2) the operation of storage to meet this commitment. We formulate two problems corresponding to two different power commitment approaches, an optimal one and a practical one, and show that the two problems are convex, allowing efficient solutions. Numerical examples show that our practical power commitment approach is close to optimal and also provide several other engineering insights.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Modeling Dynamic Spatial Correlations of Geographically Distributed Wind
           Farms and Constructing Ellipsoidal Uncertainty Sets for Optimization-Based
           Generation Scheduling
    • Authors: Pai Li;Xiaohong Guan;Jiang Wu;Xiaoxin Zhou;
      Pages: 1594 - 1605
      Abstract: The correlation information is very important for system operations with geographically distributed wind farms, and necessary for optimization-based generation scheduling methods such as the robust optimization (RO). The purpose of this paper is to provide the dynamic spatial correlations between the geographically distributed wind farms and apply them to model the ellipsoidal uncertainty sets for the robust unit commitment model. A stochastic dynamic system is established for the distributed wind farms based on a mesoscale numerical weather prediction (NWP) model, wind speed downscaling, and wind power curve models. By combining the observed wind generation measurements, a dynamic backtracking framework based on the extended Kalman filter is applied to predict the wind generation and the dynamic spatial correlations for the wind farms. In case studies, the new method is tested on actual wind farms and compared with the Gaussian copula method. The testing results validate the effectiveness of the new method. It is shown that the new method can provide more favorable interval forecasts for the aggregate wind generation than the Gaussian copula method in the entire forecast horizon, and by using the predicted spatial correlations, we can obtain more accurate ellipsoidal uncertainty sets than the Gaussian copula method and the frequently used budget uncertainty set (BUS).
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Impact of Second-Generation Plug-In Battery Electric Vehicles on the Aging
           of Distribution Transformers Considering TOU Prices
    • Authors: Assolami; Y.O.;Morsi, W.G.;
      Pages: 1606 - 1614
      Abstract: This paper investigates the impact of second-generation (SG) plug-in battery electric vehicles (PBEVs) on distribution transformers insulation life considering the time-of-use (TOU) prices. The effect of dual Level 2 charging, 3.7kW, and 6.6kW on the loss of life (LOL) of a distribution transformer is also studied. The LOL results demonstrating the effectiveness of SG PBEVs charging as two clusters versus one cluster are discussed and conclusions are drawn.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Market Mechanisms for Buying Random Wind
    • Authors: Wenyuan Tang;Jain; R.;
      Pages: 1615 - 1623
      Abstract: The intermittent nature of wind power leads to the question of how wind power producers can participate in a deregulated electricity market. In the proposed auction paradigm, wind farms bid probability distributions of generation, instead of bidding cost functions as thermal units do. Our focus is to design incentive compatible mechanisms that elicit truthful information of strategic agents who supply stochastic resource. We first study the aggregators problem of how to select the wind farms, which have the most desirable distributions. We then study the independent system operators (ISOs) problem of how to price wind energy for stochastic economic dispatch.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Reconstructing Operating Reserve: Flexibility for Sustainable Power
    • Authors: Nosair; H.;Bouffard, F.;
      Pages: 1624 - 1637
      Abstract: Traditionally, the planning of operating reserve has been done in terms of capacity and average constant ramping requirements, whereas the newly emerging concept of power system flexibility puts emphasis on resources maneuverability, as well as accurately capturing the intra-hourly variability and uncertainty resulting from significant penetration of renewable power generation. However, the traditional reserve paradigm is deemed impeding to the notion of flexibility, whereas there is yet to be a proper way of defining power system flexibility. To that end, we rethink the fundamental meaning of reserve with respect to the emerging concept of flexibility and present a new flexibility modeling framework. We characterize flexibility provision and flexibility requirements via dynamical envelopes that can reflect the higher order dynamics of power system resources and those of variability and uncertainty. We assert that flexibility adequacy is directly related to how well the aggregate flexibility envelope formed by flexibility resources encloses the flexibility requirement envelope and its dynamics over operational planning horizons. An optimal flexibility planning problem with envelopes is formulated, followed by examples involving unit commitment and economic dispatch.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • Transient Stability Augmentation of PV/DFIG/SG-Based Hybrid Power System
           by Nonlinear Control-Based Variable Resistive FCL
    • Authors: Kamal Hossain; M.;Ali, M.H.;
      Pages: 1638 - 1649
      Abstract: This paper proposes three nonlinear controllers such as fuzzy logic controller (FLC), static nonlinear controller (SNC), and adaptive-network-based fuzzy inference system (ANFIS)-based variable resistive-type fault current limiter (VR-FCL) to augment the transient stability of a large-scale hybrid power system consisting of a doubly fed induction generator (DFIG)-based wind farm, a photovoltaic (PV) plant, and a synchronous generator (SG). Appropriate resistance generation of the VR-FCL during a grid fault to provide better transient stability is the main contribution of the work. The effectiveness of the proposed control methods in improving the transient stability of the hybrid power network is verified by applying both balanced and unbalanced faults in one of the double circuit transmission lines connected to the system. Simulation results show that the proposed FLC-, SNC-, or ANFIS-based VR-FCL are effective in improving the transient stability of the studied hybrid system. Moreover, all the proposed methods exhibit almost similar performance. Therefore, any of the methods can be chosen for the transient stability enhancement of the hybrid power system.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • A Multistate Markov Model for Dimensioning Solar Powered Cellular Base
    • Authors: Chamola; V.;Sikdar, B.;
      Pages: 1650 - 1652
      Abstract: The dimensioning of photovoltaic (PV) panel and battery sizes is one of the major issues regarding the design of solar powered cellular base stations (BSs). This letter proposes a multistate Markov model for the hourly harvested solar energy to determine the cost optimal PV panel and battery dimensions for a given tolerable outage probability at a cellular BS.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
  • 2015 Index IEEE Transactions on Sustainable Energy Vol. 6
    • Pages: 1653 - 1678
      Abstract: Presents the 2015 Subject/Author index for this issue of the publication.
      PubDate: Oct. 2015
      Issue No: Vol. 6, No. 4 (2015)
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