Multi-objective optimization method of microgrid based on fuzzy clustering analysis and model recognition

被引：0
作者：
Zhao J. [1 ]
Qiu X. [1 ]
Ma J. [1 ]
Chen K. [1 ]
机构：
[1] Intelligent Electric Power Grid Key Laboratory of Sichuan Province(Sichuan University), Chengdu, 610065, Sichuan Province
来源：
Dianwang Jishu/Power System Technology | 2016年 / 40卷 / 08期
关键词：
Fuzzy clustering; Fuzzy model identification; Microgrid; Multi-objective optimization;
D O I：
10.13335/j.1000-3673.pst.2016.08.010
中图分类号：
学科分类号：
摘要：
In order to improve traditional multi-objective particle swarm optimization algorithm (MOPSO), multi-objective particle swarm optimization algorithm based on Fuzzy Clustering (FCMOPSO) is proposed considering economy, environment and battery storage capacity in microgrid scheduling process. Fuzzy clustering analysis is used to find optimal solution of each generation. Compared with MOPSO, FCMOPSO enhances stability and global search ability of the algorithm and makes Pareto distribution in optimization results more uniform. After Pareto optimal solution set is obtained, according to importance of each target in different conditions, optimal solution is found out from Pareto optimal solution set with fuzzy model. Finally, effectiveness and feasibility of the proposed algorithm are verified with a typical microgrid in Europe. © 2016, Power System Technology Press. All right reserved.
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页码：2316 / 2323
页数：7
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