Active Distribution Network Reconfiguration Based on Modified Invasive Weed Optimization Algorithm

被引：0
|
作者：
Shi J. [1 ]
Yuan D. [1 ]
Xue F. [2 ]
Ma L. [1 ]
Yang T. [1 ]
机构：
[1] School of Electrical and Information Engineering, Tianjin University, Tianjin
[2] State Grid Ningxia Electric Power Research Institute, Yinchuan
来源：
Shi, Jiying (eesjy@163.com) | 2018年 / Tianjin University卷 / 51期
基金：
中国国家自然科学基金;
关键词：
Active network reconfiguration; Distributed generation; Environmental benefits; Modified invasive weed optimization algorithm;
D O I：
10.11784/tdxbz201709058
中图分类号：
学科分类号：
摘要：
In view of active distribution network with distributed generation(DG)reconfiguration problem, a multi-scene reconfiguration model considering optimizing DG output is established and the modified invasive weed optimization(MIWO)algorithm is proposed to solve the model. Considering operation benefit of distribution system and environmental benefit, the model is built to get reconfiguration objective function to minimize active power loss, node voltage deviation, load balancing, environmental cost of pollutant emission and the costs of abandoning the wind and the light. Based on modified invasive weed optimization algorithm, the proposed algorithm designed initial population selection mechanism for reconfiguration problem to optimize initial value generated randomly, introduced process of Lévy flight and quasi hamming distance determination to maintain population diversity and avoid local optimization, and the proposed seed quantities adjusting strategy to improve convergence speed. The testing results of IEEE 33 node distribution system have confirmed the validity of the proposed model and algorithm. Compared with invasive weed optimization algorithm, particle swarm optimization algorithm and genetic algorithm, MIWO algorithm has faster convergence speed, better global search ability and stronger stability. © 2018, Editorial Board of Journal of Tianjin University(Science and Technology). All right reserved.
引用
收藏
页码：786 / 796
页数：10
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