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Appl. Sci. 2017, 7(4), 398; doi:10.3390/app7040398

Bi-Level Programming Approach for the Optimal Allocation of Energy Storage Systems in Distribution Networks

State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
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Received: 12 March 2017 / Revised: 5 April 2017 / Accepted: 12 April 2017 / Published: 14 April 2017
(This article belongs to the Special Issue Distribution Power Systems)
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Abstract

Low-CO2-emission wind generation can alleviate the world energy crisis, but intermittent wind generation influences the reliability of power systems. Energy storage might smooth the wind power fluctuations and effectively improve system reliability. The contribution of energy storage to system reliability cannot be comprehensively assessed by the installed capacity of energy storage. The primary goal of this paper is to investigate the impact of the installed location and capacity of energy storage on power system reliability. Based on a bi-level programming approach, this paper presents a bi-level energy storage programming configuration model for energy storage capacity and location configuration. For upper-level optimization, a depth search method is utilized to obtain the optimal installed location of energy storage. For the lower-level optimization, the optimal capacity of energy storage is solved to meet the system reliability requirements. The influence of the contribution of energy storage location to system reliability is analyzed. The proposed model and method are demonstrated using the RBTS-Bus6 System and Nanao (NA) island distribution system in China. The results show the effectiveness and practicability of the proposed model and method. View Full-Text
Keywords: location configuration; energy storage system; optimal allocation; bi-level programming; reliability location configuration; energy storage system; optimal allocation; bi-level programming; reliability
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Shi, N.; Luo, Y. Bi-Level Programming Approach for the Optimal Allocation of Energy Storage Systems in Distribution Networks. Appl. Sci. 2017, 7, 398.

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