Dynamic reconfiguration of active distribution network based on information entropy of time intervals

被引：0
|
作者：
Zhao J. [1 ]
Niu H. [1 ]
Wang Y. [1 ]
机构：
[1] College of Information and Electrical Engineering, China Agricultural University, Haidian District, Beijing
来源：
Dianwang Jishu/Power System Technology | 2017年 / 41卷 / 02期
关键词：
Active distribution network; Decimal hybrid invasive weed optimization algorithm; Dynamic reconfiguration; Electric vehicle; Information entropy;
D O I：
10.13335/j.1000-3673.pst.2016.2381
中图分类号：
学科分类号：
摘要：
With increasing proportion of electric vehicles and distributed generations such as wind power and photovoltaic power, dynamic reconfiguration method based on information entropy of time intervals is proposed. Firstly, Monte Carlo simulation method is used to combine daily load curve, wind/solar power curve and electric vehicle charging curve, forming equivalent daily load curve. Then equivalent load curve segmentation based on information entropy time division is proposed. A dynamic reconfiguration model with the lowest daily loss cost is established. Then a decimal hybrid algorithm based on invasive weed optimization algorithm is proposed to solve this model. Intersections and variations are added into the algorithm. Finally, simulation results of IEEE-33 nodes show that the proposed method can automatically partition segmentation scheme conforming to curve trend, and its loss cost is obviously reduced after dynamic reconfiguration. © 2017, Power System Technology Press. All right reserved.
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收藏
页码：402 / 408
页数：6
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