Optimum Sizing of Distributed Generation and Storage Capacity in Smart Households

In the near future, a smart grid will accommodate customers who are prepared to invest in generation-battery systems and employ energy management systems in order to cut down on their electricity bills. The main objective of this paper is to determine the optimum capacity of a customer's distributed-generation system (such as a wind turbine) and battery within the framework of a smart grid. The proposed approach involves developing an electricity management system based on stochastic variables, such as wind speed, electricity rates, and load. Then, a hybrid stochastic method based on Monte Carlo simulation and particle swarm optimization is proposed to determine the optimum size of the wind generation-battery system. Several sensitivity analyses demonstrate the proper performance of the proposed method in different conditions.

[1]  W. R. Powell,et al.  An analytical expression for the average output power of a wind machine , 1981 .

[2]  Ziyad M. Salameh,et al.  Methodology for optimally sizing the combination of a battery bank and PV array in a wind/PV hybrid system , 1996 .

[3]  A. Louche,et al.  Autonomous photovoltaic systems: Influences of some parameters on the sizing: Simulation timestep, input and output power profile , 1996 .

[4]  Roy Billinton,et al.  Determination of the optimum site-matching wind turbine using risk-based capacity benefit factors , 1999 .

[5]  Scott J. Benson, Sohrab Asgarpoor A Fuzzy Expert System for Evaluation of Demand-Side Management Alternatives , 2000 .

[6]  Yuhui Shi,et al.  Particle swarm optimization: developments, applications and resources , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[7]  A. Louche,et al.  Decentralized wind energy systems providing small electrical loads in remote areas , 2001 .

[8]  Ali Naci Celik,et al.  Optimisation and techno-economic analysis of autonomous photovoltaic–wind hybrid energy systems in comparison to single photovoltaic and wind systems , 2002 .

[9]  P. McSharry,et al.  Probabilistic forecasts of the magnitude and timing of peak electricity demand , 2005, IEEE Transactions on Power Systems.

[10]  Computer Aided Home Energy Management system , 2005 .

[11]  A. Borison,et al.  Forecasting Long-Run Electricity Prices , 2006 .

[12]  R. DeBlasio,et al.  Advancing Smart Grid Interoperability and Implementing NIST's Interoperability Roadmap , 2007 .

[13]  John Dalsgaard Sørensen,et al.  Optimal, reliability-based turbine placement in offshore wind turbine parks , 2007 .

[14]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[15]  G. Venkataramanan,et al.  Optimal Technology Selection and Operation of Commercial-Building Microgrids , 2008, IEEE Transactions on Power Systems.

[16]  Aleksandar Lazinica Particle Swarm Optimization , 2009 .

[17]  Orhan Ekren,et al.  Break-even analysis and size optimization of a PV/wind hybrid energy conversion system with battery storage - A case study , 2009 .

[18]  Ellips Masehian,et al.  Particle Swarm Optimization Methods, Taxonomy and Applications , 2009 .

[19]  Ian Beausoleil-Morrison,et al.  Synthetically derived profiles for representing occupant-driven electric loads in Canadian housing , 2009 .

[20]  K. Cory,et al.  Wind Levelized Cost of Energy: A Comparison of Technical and Financing Input Variables , 2009 .

[21]  Kenneth S. Smith,et al.  Smart Grid technology review within the Transmission and Distribution sector , 2010, 2010 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe).

[22]  Jianhui Wang,et al.  Smart Transmission Grid: Vision and Framework , 2010, IEEE Transactions on Smart Grid.

[23]  Santanu Bandyopadhyay,et al.  Optimum sizing of wind-battery systems incorporating resource uncertainty , 2010 .

[24]  Ryuichi Yokoyama,et al.  A study of optimal capacity of PV and battery energy storage system distributed in demand side , 2010, 45th International Universities Power Engineering Conference UPEC2010.

[25]  Rob J Hyndman,et al.  Density Forecasting for Long-Term Peak Electricity Demand , 2010, IEEE Transactions on Power Systems.

[26]  P. Siano,et al.  Combined Operations of Renewable Energy Systems and Responsive Demand in a Smart Grid , 2011, IEEE Transactions on Sustainable Energy.

[27]  Peter Palensky,et al.  Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads , 2011, IEEE Transactions on Industrial Informatics.

[28]  Andrea Schröder,et al.  Modeling Storage and Demand Management in Electricity Distribution Grids , 2011 .

[29]  Susan M. Schoenung,et al.  Energy storage systems cost update : a study for the DOE Energy Storage Systems Program. , 2011 .

[30]  Kaigui Xie,et al.  Determination of the Optimum Capacity and Type of Wind Turbine Generators in a Power System Considering Reliability and Cost , 2011, IEEE Transactions on Energy Conversion.

[31]  Qiang Fu,et al.  Microgrid Generation Capacity Design With Renewables and Energy Storage Addressing Power Quality and Surety , 2012, IEEE Transactions on Smart Grid.

[32]  Zhi Chen,et al.  Real-Time Price-Based Demand Response Management for Residential Appliances via Stochastic Optimization and Robust Optimization , 2012, IEEE Transactions on Smart Grid.

[33]  Shing-Chow Chan,et al.  Demand Response Optimization for Smart Home Scheduling Under Real-Time Pricing , 2012, IEEE Transactions on Smart Grid.

[34]  D. Anair,et al.  State of Charge Electric Vehicles' Global Warming Emissions and Fuel-Cost Savings across the United States - Prepublication Version - , 2012 .

[35]  Thillainathan Logenthiran,et al.  Demand Side Management in Smart Grid Using Heuristic Optimization , 2012, IEEE Transactions on Smart Grid.

[36]  Mariesa L. Crow,et al.  Pricing and Control in the Next Generation Power Distribution System , 2012, IEEE Transactions on Smart Grid.

[37]  Z. Benhachani,et al.  Optimal sizing of a solar-wind hybrid system supplying a farm in a semi-arid region of Algeria , 2012, 2012 47th International Universities Power Engineering Conference (UPEC).

[38]  Munther A. Dahleh,et al.  Volatility of Power Grids Under Real-Time Pricing , 2011, IEEE Transactions on Power Systems.

[39]  J. M. Sloughter,et al.  Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging , 2010 .

[40]  Manuel D. Rossetti Simulation Modeling and Arena , 2015 .