Optimal Allocation of Energy Storage System Considering Multi-Correlated Wind Farms

Shuli Wen, Hai Lan, Qiang Fu, David C. Yu, Ying-Yi Hong and Peng Cheng
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Shuli Wen: College of Automation, Harbin Engineering University, Harbin 150001, China
Hai Lan: College of Automation, Harbin Engineering University, Harbin 150001, China
Qiang Fu: Department of Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA
David C. Yu: Department of Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA
Ying-Yi Hong: Department of Electrical Engineering, Chung Yuan Christian University, Chung Li District, Taoyuan City 32023, Taiwan
Peng Cheng: College of Automation, Harbin Engineering University, Harbin 150001, China

Energies, 2017, vol. 10, issue 5, 1-16

Abstract: With the increasing penetration of wind power, not only the uncertainties but also the correlation among the wind farms should be considered in the power system analysis. In this paper, Clayton-Copula method is developed to model the multiple correlated wind distribution and a new point estimation method (PEM) is proposed to discretize the multi-correlated wind distribution. Furthermore, combining the proposed modeling and discretizing method with Hybrid Multi-Objective Particle Swarm Optimization (HMOPSO), a comprehensive algorithm is explored to minimize the power system cost and the emissions by searching the best placements and sizes of energy storage system (ESS) considering wind power uncertainties in multi-correlated wind farms. In addition, the variations of load are also taken into account. The IEEE 57-bus system is adopted to perform case studies using the proposed approach. The results clearly demonstrate the effectiveness of the proposed algorithm in determining the optimal storage allocations considering multi-correlated wind farms.

Keywords: multi-correlated wind distribution; Clayton-Copula method; point estimation method (PEM); energy storage system (ESS); multi-objective particle swarm optimization (MOPSO) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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