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Appl. Sci. 2017, 7(2), 163; doi:10.3390/app7020163

Multi-Objective Configuration Optimization of a Hybrid Energy Storage System

Hubei Provincial Collaborative Innovation Center for New Energy Microgrid (China Three Gorges University), Yichang 443002, China
College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China
Author to whom correspondence should be addressed.
Academic Editor: Luisa F. Cabeza
Received: 5 January 2017 / Accepted: 6 February 2017 / Published: 13 February 2017
(This article belongs to the Section Energy)
View Full-Text   |   Download PDF [2667 KB, uploaded 23 February 2017]   |  


This study aims to investigate multi-objective configuration optimization of a hybrid energy storage system (HESS). In order to maximize the stability of the wind power output with minimized HESS investment, a multi-objective model for optimal HESS configuration has been established, which proposes decreasing the installation and operation & maintenance costs of an HESS and improving the compensation satisfaction rate of wind power fluctuation. Besides, fuzzy control has been used to allocate power in the HESS for lengthening battery lifetime and ensuring HESS with enough energy to compensate the fluctuation of the next time interval. Instead of converting multiple objectives into one, a multi-objective particle swarm optimization with integration of bacteria quorum sensing and circular elimination (BC-MOPSO) has been applied to provide diverse alternative solutions. In order to illustrate the feasibility and effectiveness of the proposed model and the application of BC-MOPSO, simulations along with analysis and discussion are carried out. The results verified the feasibility and effectiveness of the proposed approach. View Full-Text
Keywords: wind power; hybrid energy storage system; multi-objective particle swarm optimization wind power; hybrid energy storage system; multi-objective particle swarm optimization

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Cheng, S.; Sun, W.-B.; Liu, W.-L. Multi-Objective Configuration Optimization of a Hybrid Energy Storage System. Appl. Sci. 2017, 7, 163.

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