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		<title><![CDATA[ Sustainable Energy, IEEE Transactions on - new TOC ]]></title>
		<link>http://ieeexplore.ieee.org</link>
		<description>TOC Alert for Publication# 5165391 </description>
		<year>2013</year>
		<month>May      </month>
		<day>16</day>
		<item>
			<title><![CDATA[Table of contents]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481613]]></link>
			<description><![CDATA[Presents the cover/table of contents for this issue of the periodical.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481613]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>C1</startPage>
			<endPage>277</endPage>
			<fileSize>238</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[IEEE Transactions on Sustainable Energy]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481517]]></link>
			<description><![CDATA[Provides a listing of current staff, committee members and society officers.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481517]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>C2</startPage>
			<endPage>C2</endPage>
			<fileSize>136</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[Model of Photovoltaic Power Plants for Performance Analysis and Production Forecast]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6324407]]></link>
			<description><![CDATA[A photovoltaic (PV) plant model is presented. It is based on a detailed electrothermal description of the panels forming strings that, in turn, form the power plant. It accounts for environmental working conditions, such as temperature and wind speed, and specific plant configuration, such as plant topology and power losses due to interconnections. The input variables of the model are the ambient temperature, irradiance, and wind speed. The model derives the working temperature of the panel taking into account also the power conversion performed by the panel; the electrical operating point is determined by simulating the actions done by the maximum power point tracker that operates at plant level. This model has been tested using a large database of experimental data from industrial PV plants characterized by power levels ranging from 250 kW to 1 MW. As shown, the model is capable to predict power production when &#x201C;fed&#x201D; by forecast irradiance, ambient temperature, and wind speed data.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6324407]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>278</startPage>
			<endPage>285</endPage>
			<fileSize>1517</fileSize>
			<authors><![CDATA[Bizzarri, F.;Bongiorno, M.;Brambilla, A.;Gruosso, G.;Gajani, G.S.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Evaluation of a Hybrid Power Plant Comprising Used EV-Batteries to Complement Wind Power]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6331027]]></link>
			<description><![CDATA[This paper investigates the potential of using secondhand electric vehicle (EV) batteries to provide storage in a hybrid wind battery plant (HWBP). A number of used Li-ion EV batteries are assumed connected to an existing wind park operating on the noninterconnected island of Crete. The optimal size of the hybrid extension is determined using genetic algorithms (GAs). The potential revenues that can be achieved by the HWBP from its participation in the electricity market are estimated. Results indicate that the proposed business model is economically beneficial in case rejected wind energy is stored for later use. Profit margin varies according to the price of oil consumed by the thermal units whose energy is substituted by the output of the HWBP.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6331027]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>286</startPage>
			<endPage>293</endPage>
			<fileSize>1089</fileSize>
			<authors><![CDATA[Alimisis, V.;Hatziargyriou, N.D.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Probabilistic Load Flow Method Based on Nataf Transformation and Latin Hypercube Sampling]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6338334]]></link>
			<description><![CDATA[This paper proposed a probabilistic load flow method that can address the correlated power sources and loads. The proposed probabilistic load flow method is based on the Nataf transformation and the Latin Hypercube Sampling. The main advantage of the proposed method is that high accurate solution can be obtained with less computation. Also, it is almost unconstrained for the probability distributions of the input random variables. Considering the uncertainties of correlated wind power, solar energy and loads, the effectiveness and the accuracy of the proposed probabilistic load flow method are verified by the comparative tests in a modified IEEE 14-bus system and a modified IEEE 118-bus system.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6338334]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>294</startPage>
			<endPage>301</endPage>
			<fileSize>1517</fileSize>
			<authors><![CDATA[Yan Chen;Jinyu Wen;Shijie Cheng;]]></authors>
		</item>
		<item>
			<title><![CDATA[Classification of Power Quality Disturbances Due to Environmental Characteristics in Distributed Generation System]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6341874]]></link>
			<description><![CDATA[The interconnection of the renewable-resources-based distributed generation (DG) system to the existing power system could lead to power quality (PQ) problems, degradation in system reliability, and other associated issues. This paper presents the classification of PQ disturbances caused not only by change in load but also by environmental characteristics such as change in solar insolation and wind speed. Various forms of sag and swell occurrences caused by change in load, variation in wind speed, and solar insolation are considered in the study. Ten different statistical features extracted through S-transform are used in the classification step. The PQ disturbances in terms of statistical features are classified distinctly by use of modular probabilistic neural network (MPNN), support vector machines (SVMs), and least square support vector machines (LS-SVMs) techniques. The classification study is further supported by experimental signals obtained on a prototype setup of wind energy system and PV system. The accuracy and reliability of classification techniques is also assessed on signals corrupted with noise.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6341874]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>302</startPage>
			<endPage>313</endPage>
			<fileSize>2331</fileSize>
			<authors><![CDATA[Ray, P.K.;Mohanty, S.R.;Kishor, N.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Fault Ride-Through Capability of Cascaded Current-Source Converter-Based Offshore Wind Farm]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6341875]]></link>
			<description><![CDATA[This paper presents a novel fault ride-through (FRT) strategy for the permanent-magnet synchronous generator (PMSG)-based offshore wind farm, where cascaded current- source converters (CSCs) are employed on both the generator- and grid-side. The inherent short-circuit operating capability of the CSC is used to develop the FRT strategy, and at the same time, the grid-side converters fulfill the demanding reactive power requirement imposed by recent grid codes. Intensive simulation results are provided to ensure the validity and feasibility of the proposed FRT method. Moreover, the inherent short-circuit operating capability of the CSC contributes to a great operating flexibility for the proposed wind farm. Specifically, the faulty turbine-generator unit can be easily isolated from the cascaded system without affecting the operation of other series interconnected wind turbines. Both simulation and experimental verifications are provided for the operating flexibility of the cascaded CSC-based wind farm by isolating one wind generator from the system.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6341875]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>314</startPage>
			<endPage>323</endPage>
			<fileSize>2214</fileSize>
			<authors><![CDATA[Popat, M.;Bin Wu;Zargari, N.R.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Optimal Active Control and Optimization of a Wave Energy Converter]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6353624]]></link>
			<description><![CDATA[This paper investigates optimal active control schemes applied to a point absorber wave energy converter within a receding horizon fashion. A variational formulation of the power maximization problem is adapted to solve the optimal control problem. The optimal control method is shown to be of a bang-bang type for a power takeoff mechanism that incorporates both linear dampers and active control elements. We also consider a direct transcription of the optimal control problem as a general nonlinear program. A variation of the projected gradient optimization scheme is formulated and shown to be feasible and computationally inexpensive compared to a standard NLP solver. Since the system model is bilinear and the cost function is not convex quadratic, the resulting optimization problem is not a quadratic program. Results will be compared with an optimal command latching method to demonstrate the improvement in absorbed power. All time domain simulations are generated under irregular sea conditions.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6353624]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>324</startPage>
			<endPage>332</endPage>
			<fileSize>1670</fileSize>
			<authors><![CDATA[Abraham, E.;Kerrigan, E.C.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Solar Power Prediction Using Interval Type-2 TSK Modeling]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6355705]]></link>
			<description><![CDATA[The random nature of solar energy resources is one of the obstacles to their large-scale proliferation in power systems. The most practical way to predict this renewable source of energy is to use meteorological data. However, such data are usually provided in a qualitative form that cannot be exploited using traditional quantitative methods but which can be modeled using fuzzy logic. This paper proposes type-1 and interval type-2 Takagi-Sugeno-Kang (TSK) fuzzy systems for the modeling and prediction of solar power plants. The paper considers TSK models with type-1 antecedents and crisp consequents, type-1 antecedents and consequents, and type-2 antecedents and crisp consequents. The design methodology for tuning the antecedents and consequents of each model is described. Finally, input-output data sets from a solar plant are used to obtain the three TSK models and their prediction results are compared to results from the literature. The results show that type-2 TSK models with type2 antecedents and crisp consequents provide the best performance based on the solar plant data.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6355705]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>333</startPage>
			<endPage>339</endPage>
			<fileSize>850</fileSize>
			<authors><![CDATA[Jafarzadeh, S.;Fadali, M.S.;Evrenosoglu, C.Y.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Optimization of Subcell Interconnection for Multijunction Solar Cells Using Switching Power Converters]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6353243]]></link>
			<description><![CDATA[A multijunction solar cell can extract higher solar energy compared to a single junction cell by splitting the solar spectrum. Although extensive research on solar cell efficiency enhancement is in place, limited research materials are available to identify the optimum interconnection of multijunction solar subcells using power electronic circuits. Multijunction solar cells could be grouped into two main categories: vertical multijunction (VMJ) solar cells and lateral multijunction (LMJ) solar cells. In this paper, a detailed study to identify the optimum interconnection method for various multijunction solar cells has been conducted. The authors believe that the conducted research in this area is very limited, and an effective power electronic circuit could substantially improve the efficiency and utilization of a photovoltaic (PV) power system constructed from multijunction solar cells. A multiple input dc-to-dc boost converter has been used to demonstrate the advantage of the proposed interconnection technique. In order to ensure maximum power point (MPP) operation, a particle swarm optimization (PSO) algorithm has been applied needing only one MPP control for multiple solar modules resulting in cost and complexity reduction. The PSO algorithm has the potential to track the global maxima of the system even under complex illumination situations. A complete functional system with the implementation of the proposed algorithm has been presented in this paper with relevant experimental results.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6353243]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>340</startPage>
			<endPage>349</endPage>
			<fileSize>1730</fileSize>
			<authors><![CDATA[Alam, M.K.;Faisal Khan;Imtiaz, A.M.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Steady-State Analysis of Maximum Photovoltaic Penetration Levels on Typical Distribution Feeders]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6357275]]></link>
			<description><![CDATA[This paper presents simulation results for a taxonomy of typical distribution feeders with various levels of photovoltaic (PV) penetration. For each of the 16 feeders simulated, the maximum PV penetration that did not result in a steady-state voltage or current violation is presented for several PV location scenarios: clustered near the feeder source, clustered near the midpoint of the feeder, clustered near the end of the feeder, randomly located, and evenly distributed. In addition, the maximum level of PV is presented for single, large PV systems at each location. Maximum PV penetration was determined by requiring that feeder voltages stay within ANSI Range A and that feeder currents stay within the ranges determined by overcurrent protection devices. Generation ramp rates, protection and coordination, and other factors that may impact maximum PV penetrations are not considered here. Simulations were run in GridLAB-D using hourly time steps over a year with randomized load profiles based on utility data and typical meteorological year weather data. For 86% of the 336 cases simulated, maximum PV penetration was at least 30% of peak load.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6357275]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>350</startPage>
			<endPage>357</endPage>
			<fileSize>1215</fileSize>
			<authors><![CDATA[Hoke, A.;Butler, R.;Hambrick, J.;Kroposki, B.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Power Flow Control and Stability Improvement of Connecting an Offshore Wind Farm to a One-Machine Infinite-Bus System Using a Static Synchronous Series Compensator]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6365290]]></link>
			<description><![CDATA[This paper presents the stability improvement and power-flow control results of a DFIG-based offshore wind farm (OWF) connected to a one-machine infinite-bus (OMIB) system using a static synchronous series compensator (SSSC). An oscillation damping controller (ODC) of the proposed SSSC is designed by using modal control theory to render proper damping to the dominant mode of the studied synchronous generator (SG). A frequency-domain approach based on a linearized system model using eigenvalue analysis is accomplished. A time-domain scheme based on a nonlinear system model subject to a disturbance is also performed. It can be concluded from the simulation results that the proposed SSSC joined with the designed ODC can effectively improve the stability of the studied OMIB system with an OWF under various disturbances. The inherent low-frequency oscillations of the OMIB system can also be effectively suppressed by the proposed control scheme.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6365290]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>358</startPage>
			<endPage>369</endPage>
			<fileSize>2631</fileSize>
			<authors><![CDATA[Li Wang;Quang-Son Vo;]]></authors>
		</item>
		<item>
			<title><![CDATA[Sensitivity-Indices-Based Risk Assessment of Large-Scale Solar PV Investment Projects]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6381513]]></link>
			<description><![CDATA[Large-scale solar photovoltaic (PV) generation is now a viable, economically feasible and clean energy supply option. Incentive schemes, such as the Feed-in-Tariff (FIT) in Ontario, have attracted large-scale investments in solar PV generation. In a previous work, the authors presented an investor-oriented planning model for optimum selection of solar PV investment decisions. In this paper, a method for determining the sensitivity indices, based on the application of duality theory on the Karush-Kuhn-Tucker (KKT) optimality conditions, pertaining to the solar PV investment model is presented. The sensitivity of the investors' profit to various parameters, for a case study in Ontario, Canada are presented and discussed and these are found to be very close to those obtained using the Monte Carlo simulation and finite-difference (individual parameter perturbation) based approaches. Furthermore, a novel relationship is proposed between the sensitivity indices and the investor's profit for a given confidence level to evaluate the risk for an investor in solar PV projects.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6381513]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>370</startPage>
			<endPage>378</endPage>
			<fileSize>1479</fileSize>
			<authors><![CDATA[Das, I.;Bhattacharya, K.;Canizares, C.;Muneer, W.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Wind Power Fluctuation Smoothing Controller Based on Risk Assessment of Grid Frequency Deviation in an Isolated System]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6387354]]></link>
			<description><![CDATA[Wind power fluctuation raises the security concern of grid frequency deviation, especially for an isolated power system. Thus, better control methodology needs to be developed to smooth the fluctuation without excessive spillage. Based on an actual industrial power system, this paper proposes a smoothing controller to suppress the power fluctuation from doubly-fed induction generator (DFIG)-based wind farm. This controller consists of three main functionality components: risk assessment model, wind turbine rotor speed optimizer, and rotor speed upper limiter. In order to avoid unnecessary energy loss, this paper designs a risk assessment model of grid frequency deviation, which is capable of locally estimating the maximum grid frequency deviation risk of the next dispatch cycle. A wind turbine speed optimizer then uses the estimated frequency deviation risk to search for the optimal power curve with reduced output so that a trade-off between fluctuation smoothing and energy loss is achieved. Subsequently, the controller limits the maximum rotor speed to shift down the power curve of wind power plant based on the optimal wind turbine rotor speed. Therefore, the power fluctuation is smoothed along with the down-regulated power curve. A numerical case study demonstrates the effectiveness and economy of this smoothing controller for the studied isolated system.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6387354]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>379</startPage>
			<endPage>392</endPage>
			<fileSize>2260</fileSize>
			<authors><![CDATA[Jin Lin;Yuanzhang Sun;Yonghua Song;Wenzhong Gao;Sorensen, P.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Planning Pumped Storage Capacity for Wind Power Integration]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6392322]]></link>
			<description><![CDATA[Pumped storage can provide some of the flexibility that power system operators need to balance load and generation in an uncertain environment, and thus enhance a power system's ability to incorporate wind power. Since the process of balancing wind power involves various combinations of wind generation and loads, the amount of pumped storage capacity needed should be evaluated using a substantial number of scenarios. This paper describes a chronological production simulation platform and its application in planning pumped storage capacity for the Jiangsu (China) provincial power system. The daily dispatching of various types of units is simulated using a unit commitment module. A simulation of wind farm operation is incorporated in this module to take into account the effect of its variability on daily dispatching. A detailed cost model for thermal generating units provides an accurate estimate of the benefits of pumped storage. Simulation results clearly show how much generation cost and wind power curtailment should be expected for different amounts of pumped storage capacity. A comparison between the operating and investment costs is then used to determine the optimal pumped storage capacity. Finally, various sensitivity analyses are performed to assess the effect of key parameters on this optimal capacity.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6392322]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>393</startPage>
			<endPage>401</endPage>
			<fileSize>1414</fileSize>
			<authors><![CDATA[Ning Zhang;Chongqing Kang;Kirschen, D.S.;Qing Xia;Weimin Xi;Junhui Huang;Qian Zhang;]]></authors>
		</item>
		<item>
			<title><![CDATA[A Novel Operation and Control Strategy for a Standalone Hybrid Renewable Power System]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6392321]]></link>
			<description><![CDATA[This paper proposes a novel operation and control strategy for a renewable hybrid power system for a standalone operation. The proposed hybrid system consists of a wind turbine, a fuel cell, an electrolyzer, a battery storage unit, and a set of loads. The overall control strategy is based on a two-level structure. The top level is the energy management and power regulation system. Depending on wind and load conditions, this system generates reference dynamic operating points to low level individual subsystems. The energy management and power regulation system also controls the load scheduling operation during unfavorable wind conditions under inadequate energy storage in order to avoid a system blackout. Based on the reference dynamic operating points of the individual subsystems, the local controllers control the wind turbine, fuel cell, electrolyzer, and battery storage units. The proposed control system is implemented in MATLAB Simpower software and tested for various wind and load conditions. Results are presented and discussed.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6392321]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>402</startPage>
			<endPage>413</endPage>
			<fileSize>2522</fileSize>
			<authors><![CDATA[Haruni, A.M.O.;Negnevitsky, M.;Haque, M.E.;Gargoom, A.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Use of Ultracapacitors and Batteries for Efficient Energy Management in Wind&#x2013;Diesel Hybrid System]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6392923]]></link>
			<description><![CDATA[The interconnection of the wind generator (WG) and the diesel generator (DG) induces some interactions on the common coupling point. These interactions are studied in this paper with the aim of identifying the system limits in performance and proposing an alternative solution. Due to the fast fluctuations of the WG and the DG slow dynamics, ultracapacitors and batteries are used for improving the hybrid system performances and reducing the fuel consumption. The dc-bus voltage is controlled by the diesel engine while providing a smoothed current. To ensure optimized life cycle cost and performance, a lifetime-estimation-based method is proposed. In this method, a rainflow counting method is applied to size the storage devices by taking into account the actual conditions of the system operation. The experimental test bench is designed in a reduced scale. Some simulations and experimental results are presented and analyzed.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6392923]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>414</startPage>
			<endPage>424</endPage>
			<fileSize>2507</fileSize>
			<authors><![CDATA[Tankari, M.A.;Camara, M.B.;Dakyo, B.;Lefebvre, G.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Fault-Tolerant Control Performance Comparison of Three- and Five-Phase PMSG for Marine Current Turbine Applications]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6395793]]></link>
			<description><![CDATA[This paper deals with the use of permanent magnet multiphase generators in marine current turbines with the aim to highlight their fault-tolerance. In this context, the performances and the fault-tolerant capabilities of a five-phase permanent magnet synchronous generator are evaluated within a marine current turbine and compared to a classical three-phase generator. For both topologies, a robust nonlinear control strategy is adopted. The adopted control consists of an adaptive control approach that combines three strategies: a maximum power point tracking (MPPT), an optimal fault-adaptive reference current generation, and high-order sliding modes. Simulations are carried-out using a Matlab/Simulink-based marine current turbine simulator to analyze the generator performances during open-circuit faults. Conclusions are then derived regarding multiphase generators' key features for marine applications.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6395793]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>425</startPage>
			<endPage>433</endPage>
			<fileSize>2388</fileSize>
			<authors><![CDATA[Mekri, F.;Ben Elghali, S.;Benbouzid, M.E.H.;]]></authors>
		</item>
		<item>
			<title><![CDATA[A Framework for Optimal Placement of Energy Storage Units Within a Power System With High Wind Penetration]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6400274]]></link>
			<description><![CDATA[This paper deals with optimal placement of the energy storage units within a deregulated power system to minimize its hourly social cost. Wind generation and load are modeled probabilistically using actual data and a curve fitting approach. Based on a model of the electricity market, we minimize the hourly social cost using probabilistic optimal power flow (POPF) then use a genetic algorithm to maximize wind power utilization over a scheduling period. A business model is developed to evaluate the economics of the storage system based on the energy time-shift opportunity from wind generation. The proposed method is used to carry out simulation studies for the IEEE 24-bus system. Transmission line constraints are addressed as a bottleneck for efficient wind power integration with higher penetration levels. Distributed storage is then proposed as a solution to effectively utilize the transmission capacity and integrate the wind power more efficiently. The potential impact of distributed storage on wind utilization is also evaluated through several case studies.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6400274]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>434</startPage>
			<endPage>442</endPage>
			<fileSize>1081</fileSize>
			<authors><![CDATA[Ghofrani, M.;Arabali, A.;Etezadi-Amoli, M.;Fadali, M.S.;]]></authors>
		</item>
		<item>
			<title><![CDATA[A Model for the Optimization of the Maintenance Support Organization for Offshore Wind Farms]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6399559]]></link>
			<description><![CDATA[Maintenance of offshore wind power plants is known to be extensive and costly. This paper presents a model for optimizing the maintenance support organization of an offshore wind farm: the location of maintenance accommodation, the number of technicians, the choice of transfer vessels, and the use of a helicopter. The model includes an analysis of a transportation strategy using alternative transportation means, a queuing model of maintenance activities, and an economic model of the maintenance support organization. An example based on a generic 100 wind turbine 5-MW wind farm is used to demonstrate the application of the model. The results show the benefit of the production losses of the different options, which enables the identification of an optimal maintenance support organization based on the reliability, logistic costs, and electricity price. The most cost-efficient maintenance support organization in the case study consists of an offshore accommodation with technicians on service 24 hours a day, 7 days a week. The solution suggests transportation by use of a crew transfer vessel equipped with a motion compensated access system.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6399559]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>443</startPage>
			<endPage>450</endPage>
			<fileSize>1278</fileSize>
			<authors><![CDATA[Besnard, F.;Fischer, K.;Tjernberg, L.B.;]]></authors>
		</item>
		<item>
			<title><![CDATA[An Index for STATCOM Placement to Facilitate Grid Integration of DER]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6407496]]></link>
			<description><![CDATA[In recent years, the penetration level of renewable-based distributed energy resource (DER) units has increased significantly. Consequently, standards have been developed and deployed demanding small DER units to operate in constant power factor mode and large DER units in voltage control mode. This results in exposing small DER units to the problem of slow voltage recovery for contingencies like faults. Hence, this paper proposes a methodology of static and dynamic reactive power compensation to avoid tripping of small DER units due to slow voltage recovery. A new sensitivity index has been developed for the placement of STATic synchronous COMpensator (STATCOM) to ensure fast voltage recovery at all the buses of interest. The case studies involving two IEEE test systems with varying size and load compositions validate the proposed methodology and index.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6407496]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>451</startPage>
			<endPage>460</endPage>
			<fileSize>1983</fileSize>
			<authors><![CDATA[Aziz, T.;Mhaskar, U.P.;Saha, T.K.;Mithulananthan, N.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Table of contents]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481512]]></link>
			<description><![CDATA[Presents the table of contents for this issue of the periodical.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481512]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>461</startPage>
			<endPage>462</endPage>
			<fileSize>208</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[Guest Editorial: Special Section on Applications of Solar Energy to Power Systems]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481518]]></link>
			<description><![CDATA[A special section in this issue of IEEE Transactions on Sustainable Energy (TSTE) is devoted to Solar Energy. This section of TSTE highlights some of the most recent research that addresses these integration challenges and presents novel solutions for the integration of solar energy into the electric power system. The Special Section in this issue contains nine papers that were selected from the forty-one papers submitted. Four of the papers in this section examine the fact that solar energy is variable in nature and could benefit from integration with energy storage. By using energy storage, solar energy can be stored during periods of high output and then used when needed. Another important aspect of integrating solar energy is the ability to forecast its power output and there are four papers that examine the latest techniques in solar forecasting. A final paper focuses on understanding the impacts of high penetrations of solar on distribution systems and development of solutions to mitigate these issues.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481518]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>463</startPage>
			<endPage>463</endPage>
			<fileSize>81</fileSize>
			<authors><![CDATA[Kroposki, B.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Battery Energy Storage Station (BESS)-Based Smoothing Control of Photovoltaic (PV) and Wind Power Generation Fluctuations]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6473871]]></link>
			<description><![CDATA[The battery energy storage station (BESS) is the current and typical means of smoothing wind- or solar-power generation fluctuations. Such BESS-based hybrid power systems require a suitable control strategy that can effectively regulate power output levels and battery state of charge (SOC). This paper presents the results of a wind/photovoltaic (PV)/BESS hybrid power system simulation analysis undertaken to improve the smoothing performance of wind/PV/BESS hybrid power generation and the effectiveness of battery SOC control. A smoothing control method for reducing wind/PV hybrid output power fluctuations and regulating battery SOC under the typical conditions is proposed. A novel real-time BESS-based power allocation method also is proposed. The effectiveness of these methods was verified using MATLAB/SIMULINK software.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6473871]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>464</startPage>
			<endPage>473</endPage>
			<fileSize>1891</fileSize>
			<authors><![CDATA[Xiangjun Li;Dong Hui;Xiaokang Lai;]]></authors>
		</item>
		<item>
			<title><![CDATA[Daily Solar Energy Estimation for Minimizing Energy Storage Requirements in PV Power Plants]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6268311]]></link>
			<description><![CDATA[This paper proposes an optimized energy management strategy (EMS) for photovoltaic (PV) power plants with energy storage (ES) based on the estimation of the daily solar energy production. This EMS produces a constant-by-hours power reference which mitigates the stochastic nature of PV production typically associated to the solar resource, and enables PV power plants to take part in the day and intraday electricity markets. The possibility of using the intraday market sessions to refine the plant's power reference paves the way to minimizing the energy capacity ratings of the ES system required to operate the PV power plant without incurring excessive production deviations. This proposal is analyzed on an annual basis using actual irradiance data and theoretical irradiance models extracted from official databases.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6268311]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>474</startPage>
			<endPage>481</endPage>
			<fileSize>1488</fileSize>
			<authors><![CDATA[Beltran, H.;Perez, E.;Aparicio, N.;Rodriguez, P.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Predictive Power Control for PV Plants With Energy Storage]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6304948]]></link>
			<description><![CDATA[This work presents a model predictive control (MPC) approach to manage in real-time the energy generated by a grid-tied photovoltaic (PV) power plant with energy storage (ES), optimizing its economic revenue. This MPC approach stands out because, when a long enough prediction horizon is used, the saturation of the ES system (ESS) can be advanced by means of a prediction model of the PV panels production. Therefore, the PV+ES power plant can modify its production so as to manage the power deviations with regard to that committed in the daily and intraday electricity markets, with the objective of reducing economic penalties. The initial power commitment is supposed in this work to be given by a higher level energy management operator. By a proper definition of its objective function, the predictive control allows us to economically optimize the PV+ES power plant performance. This control strategy is tested in simulations with actual data measured for different days with varying meteorological conditions. Results provide a good reference on the economic benefits which can be obtained thanks to the MPC introduction.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6304948]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>482</startPage>
			<endPage>490</endPage>
			<fileSize>1570</fileSize>
			<authors><![CDATA[Perez, E.;Beltran, H.;Aparicio, N.;Rodriguez, P.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Development of a Markov-Chain-Based Energy Storage Model for Power Supply Availability Assessment of Photovoltaic Generation Plants]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6298069]]></link>
			<description><![CDATA[A new Markov-chain-based energy storage model to evaluate power supply availability of photovoltaic generation is proposed. Since photovoltaic resources have high output variability subject to weather conditions, energy storage can be added in order to increase the availability of photovoltaic generation. Although adding energy storage is a promising strategy to improve the availability of photovoltaic generation, energy storage sizing to meet a certain availability must be taken into account in order to avoid over-sizing or under-sizing capacity, which are two undesirable conditions leading to increased system cost or inadequate availability, respectively. This paper proposes a new Markov-chain-based energy storage model to develop a power supply availability framework for photovoltaic generation. The proposed work models energy states in a photovoltaic-energy storage system in order to understand the nature of charge/discharge rates for energy storage that affect the system's power output. This developed Markov chain model may assist when planning both large and small-scale grid integrated photovoltaic generation because energy state's behavior of the photovoltaic-energy storage model can be used for forecasting expected power output. In addition, an example using lithium-ion batteries is given in order to explore the effects on availability of energy storage capacity degradation.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6298069]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>491</startPage>
			<endPage>500</endPage>
			<fileSize>1929</fileSize>
			<authors><![CDATA[Junseok Song;Krishnamurthy, V.;Kwasinski, A.;Sharma, R.;]]></authors>
		</item>
		<item>
			<title><![CDATA[A Wavelet-Based Variability Model (WVM) for Solar PV Power Plants]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6269913]]></link>
			<description><![CDATA[A wavelet variability model (WVM) for simulating solar photovoltaic (PV) power plant output given a single irradiance point sensor timeseries using spatio-temporal correlations is presented. The variability reduction (VR) that occurs in upscaling from the single point sensor to the entire PV plant at each timescale is simulated, then combined with the wavelet transform of the point sensor timeseries to produce a simulated power plant output. The WVM is validated against measurements at a 2-MW residential rooftop distributed PV power plant in Ota City, Japan and at a 48-MW utility-scale power plant in Copper Mountain, NV. The WVM simulation matches the actual power output well for all variability timescales, and the WVM compares well against other simulation methods.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6269913]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>501</startPage>
			<endPage>509</endPage>
			<fileSize>1870</fileSize>
			<authors><![CDATA[Lave, M.;Kleissl, J.;Stein, J.S.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Geostrophic Wind Dependent Probabilistic Irradiance Forecasts for Coastal California]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6236289]]></link>
			<description><![CDATA[Coastal California has enormous potential for rooftop solar photovoltaic (PV) energy production. To reduce grid-integration costs, accurate and certain solar energy forecasts are required. However, frequent marine layer fog and stratus conditions limit the accuracy of numerical weather prediction models, especially during the summer. Thus, irradiance uncertainty is large and probabilistic forecast intervals are generally wide. To produce narrow and meaningful forecast intervals, the correlation of uncertainty to local meteorological conditions describing synoptic-scale atmospheric flow was considered. Specifically, the direction and magnitude of geostrophic flow were used as an indicator of coastal cloud cover probability to produce regime-dependent forecast intervals. The method was tested in summer 2011 for coastal California. The forecast interval was smaller than that provided by previous methods for all except clear conditions and contained 80% of irradiance measurements.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6236289]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>510</startPage>
			<endPage>518</endPage>
			<fileSize>1267</fileSize>
			<authors><![CDATA[Mathiesen, P.;Brown, J.M.;Kleissl, J.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Aggregate Ramp Rates of Distributed Photovoltaic Systems in San Diego County]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6232480]]></link>
			<description><![CDATA[Aggregate ramp rates of 86 distributed photovoltaic (PV) systems installed in Southern California were analyzed and compared to irradiation measured at five ground stations and estimated from satellite. Irradiation data was converted to power output using a PV performance model to evaluate whether widespread on-line metering and telemetry of PV systems is necessary to track output of distributed generation for resource-adequacy applications. The satellite data were able to closely follow the aggregate power output and detect the timing of the ramps while the five weather stations were not as accurate due to smaller number and non-representative geographical distribution with respect to the PV sites. Over one year, the largest hourly aggregate ramp was a 50% increase based on the Performance Test Conditions (PTC) rating but ramps over 30% of PTC occurred only about once per day. The effects of specific meteorological conditions, such as coastal marine layer clouds and frontal system effects, on occurrence of large ramps were investigated over the area using satellite imagery. Evaporation of morning marine layer clouds caused a disproportionally large amount of up-ramps.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6232480]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>519</startPage>
			<endPage>526</endPage>
			<fileSize>1697</fileSize>
			<authors><![CDATA[Jamaly, M.;Bosch, J.L.;Kleissl, J.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Determination Method of Insolation Prediction With Fuzzy and Applying Neural Network for Long-Term Ahead PV Power Output Correction]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6473872]]></link>
			<description><![CDATA[In recent years, introduction of an alternative energy source such as solar energy is expected. However, insolation is not constant and the output of a photovoltaic (PV) system is influenced by meteorological conditions. In order to predict the power output for PV systems as accurately as possible, an insolation estimation method is required. This paper proposes the power output forecasting of a PV system based on insolation forecasting at 24 hours ahead by using weather reported data, fuzzy theory, and neural network (NN). If the suitable training data is not selected, the training process of NN tends to be unstable. The proposed technique for application of NN is trained by power output data based on fuzzy theory and weather reported data. Since the fuzzy model determines the insolation forecast data, NN will train the power output smoothly. The validity of the proposed method is confirmed by comparing the forecasting abilities on the computer simulations.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6473872]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>527</startPage>
			<endPage>533</endPage>
			<fileSize>1809</fileSize>
			<authors><![CDATA[Yona, A.;Senjyu, T.;Funabashi, T.;Chul-Hwan Kim;]]></authors>
		</item>
		<item>
			<title><![CDATA[Improved Low Voltage Grid-Integration of Photovoltaic Systems in Germany]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6213176]]></link>
			<description><![CDATA[This work discusses the technical and economical benefits of different active and reactive power control strategies for grid-connected photovoltaic systems in Germany. The aim of these control strategies is to limit the voltage rise, caused by a high local photovoltaic power feed-in and hence allow additional photovoltaic capacity to be connected to the mains. Autonomous inverter control strategies, which do not require any kind of data communication between the inverter and its environment, as well as an on-load tap changer for distribution transformers, is investigated. The technical and economical assessment of these strategies is derived from 12-month root mean square (rms) simulations, which are based on a real low voltage grid and measured dc power generation values. The results show that the provision of reactive power is an especially effective way to increase the hosting capacity of a low voltage grid for photovoltaic systems.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6213176]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>534</startPage>
			<endPage>542</endPage>
			<fileSize>2339</fileSize>
			<authors><![CDATA[Stetz, T.;Marten, F.;Braun, M.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Open Access]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481514]]></link>
			<description><![CDATA[Advertisement: This publication offers open access options for authors. IEEE open access publishing.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481514]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>543</startPage>
			<endPage>543</endPage>
			<fileSize>1156</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[IEEE Transactions Smart Grid [advertisement]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481513]]></link>
			<description><![CDATA[Advertisement: The IEEE Transactions on Smart Grid is intended to be a cross disciplinary and internationally archival journal aimed at disseminating the results of research on smart grid that relates to energy generation, transmission, distribution and delivery. The journal will publish original research on theories, technologies, design, policies, and implementation of smart grid. The Transactions SMARTGRID will welcome manuscripts on design, implementation and evaluation of energy systems that include smart grid technologies and applications. Surveys of existing work on smart grid may also be considered for publication when they propose a challenging perspective on the future of such technologies and systems. Topical issues considered by the Transactions include: Smart sensing, communication and control in energy systems; Wireless communications and advanced metering infrastructure; Smart grid for energy management in buildings and home automation; Phasor measurement unit applications for smart grid; Smart grid for plug-in vehicles and low-carbon transportation alternatives; Smart grid for cyber and physical security systems; Smart grid for distributed energy resources; Smart grid for energy savings and financial management; Smart grid in interdependent energy infrastructures; Smart grid for intelligent monitoring and outage management.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481513]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>544</startPage>
			<endPage>544</endPage>
			<fileSize>637</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[IEEE Transactions on Sustainable Energy society information]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481515]]></link>
			<description><![CDATA[Provides a listing of current committee members and society officers.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481515]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>C3</startPage>
			<endPage>C3</endPage>
			<fileSize>102</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[IEEE Power Engineering Society information for authors]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481516]]></link>
			<description><![CDATA[Provides instructions and guidelines to prospective authors who wish to submit manuscripts.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6481516]]></guid>
			<volume>4</volume>
			<issue>2</issue>
			<startPage>C4</startPage>
			<endPage>C4</endPage>
			<fileSize>113</fileSize>
			<authors><![CDATA[]]></authors>
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