Distribution Network Reconfiguration for Loss Reduction and Voltage Stability With Random Fuzzy Uncertainties of Renewable Energy Generation and Load

被引:90
作者
Wu, Huayi [1 ]
Dong, Ping [1 ]
Liu, Mingbo [1 ]
机构
[1] South China Univ Technol, Sch Elect Power, Guangzhou 510640, Peoples R China
基金
中国国家自然科学基金;
关键词
Uncertainty; Load modeling; Probability density function; Wind speed; Renewable energy sources; Linear programming; Stochastic processes; Particle swarm optimization (PSO); random fuzzy variable; renewable energy; voltage stability; DISTRIBUTION-SYSTEMS; WIND POWER; OPTIMIZATION; SOLAR;
D O I
10.1109/TII.2018.2871551
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a distribution reconfiguration framework to adapt to the distribution network considering the twofold random and fuzzy uncertainties of the wind, photovoltaic power generation, and load demand and considering the power loss reduction and voltage stability. First, the random fuzzy power output models of distributed generation and load are built based on the random fuzzy theory. Second, the corresponding objective functions are established, which are the random fuzzy expected value of active power loss and maximum probability of voltage limit. Third, the modified particle swarm optimization (MPSO) algorithm based on Kruskal algorithm is introduced for the first time to determine the optimal network topology. The Kruskal algorithm is employed to generate a radial network topology directly without checking the loops and islands. Lastly, the proposed method is applied to the IEEE33, PG&E 69-bus distribution systems, 25-bus unbalanced distribution system, as well as a real 109-bus distribution system. The results show that the proposed method has a good performance to solve distribution network reconfiguration problem.
引用
收藏
页码:5655 / 5666
页数:12
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