Adequacy and economy analysis of distribution systems integrated with Electric Energy Storage and Renewable Energy Resources

Summary form only given. The integration of Renewable Energy Resources (RER) into an existing distribution system is an important topic in dealing with energy challenge the world is facing. With rapid development of Electric Energy Storage (EES) technologies, there is a growing interest in integrating both EES and RER into power systems to improve their reliability and economy. In this paper, the adequacy and economy of distribution systems integrated with both EES and RER are assessed. A novel Model Predictive Control (MPC)-based operation strategy is presented to minimize distribution system energy purchasing cost by coordinating multiple power supplies from EES, RER and external grid. An islanding operation is implemented to improve the distribution system reliability and reduce customer interruption cost. A reliability and economy assessment framework based on sequential Monte Carlo method integrated with the MPC-based operation and islanding operation is proposed. Case studies are conducted to demonstrate the reliability and economy improvement by implementing the proposed operation strategies together with integration of EES and RER, and also investigate how EES capacity, power limit, and wind turbine generation capacity affect system reliability and economy.

[1]  A. T. Holen,et al.  Operation planning of hydrogen storage connected to wind power operating in a power market , 2006, IEEE Transactions on Energy Conversion.

[2]  N. Amjady,et al.  Day-Ahead Price Forecasting of Electricity Markets by Mutual Information Technique and Cascaded Neuro-Evolutionary Algorithm , 2009, IEEE Transactions on Power Systems.

[3]  A. Pregelj,et al.  Recloser allocation for improved reliability of DG-enhanced distribution networks , 2006, IEEE Transactions on Power Systems.

[4]  Chanan Singh,et al.  An efficient technique for reliability analysis of power systems including time dependent sources , 1988 .

[5]  X. Huo,et al.  Electricity Price Curve Modeling and Forecasting by Manifold Learning , 2008, IEEE Transactions on Power Systems.

[6]  Marija D. Ilic,et al.  Model predictive economic/environmental dispatch of power systems with intermittent resources , 2009, 2009 IEEE Power & Energy Society General Meeting.

[7]  T. Senjyu,et al.  A Novel Approach to Forecast Electricity Price for PJM Using Neural Network and Similar Days Method , 2007, IEEE Transactions on Power Systems.

[8]  V. Miranda,et al.  Entropy and Correntropy Against Minimum Square Error in Offline and Online Three-Day Ahead Wind Power Forecasting , 2009, IEEE Transactions on Power Systems.

[9]  R. Billinton,et al.  Composite System Adequacy Assessment Incorporating Large-Scale Wind Energy Conversion Systems Considering Wind Speed Correlation , 2009, IEEE Transactions on Power Systems.

[10]  Chanan Singh,et al.  Optimal scheduling and operation of load aggregators with electric energy storage facing price and demand uncertainties , 2011, 2011 North American Power Symposium.

[11]  J. Lobry,et al.  System Reliability Assessment Method for Wind Power Integration , 2008, IEEE Transactions on Power Systems.

[12]  Roy Billinton,et al.  Reliability Evaluation Considering Wind and Hydro Power Coordination , 2010, IEEE Transactions on Power Systems.

[13]  E.F. El-Saadany,et al.  Supply Adequacy Assessment of Distribution System Including Wind-Based DG During Different Modes of Operation , 2010, IEEE Transactions on Power Systems.

[14]  T. Funabashi,et al.  Next day load curve forecasting using hybrid correction method , 2005, IEEE Transactions on Power Systems.

[15]  R. Billinton,et al.  Rleliability Benefit Analysis of Adding WTG in a Distribution System , 2001, IEEE Power Engineering Review.

[16]  R. Billinton,et al.  Reliability Cost/Worth Associated With Wind Energy and Energy Storage Utilization in Electric Power Systems , 2008, Proceedings of the 10th International Conference on Probablistic Methods Applied to Power Systems.

[17]  R. Buizza,et al.  Neural Network Load Forecasting with Weather Ensemble Predictions , 2002, IEEE Power Engineering Review.

[18]  N.D. Hatziargyriou,et al.  An Advanced Statistical Method for Wind Power Forecasting , 2007, IEEE Transactions on Power Systems.