Parallel Canonical Differential Evolutionary Particle Swarm Optimization for Voltage and Reactive Power Control

被引:1
|
作者
Azuma, Daichi [1 ]
Yoshida, Hotaka [1 ]
Fukuyama, Yoshikazu [1 ]
机构
[1] Meiji Univ, Tokyo, Japan
来源
IFAC PAPERSONLINE | 2018年 / 51卷 / 28期
关键词
Voltage and reactive power control; Power system; Evolutionary computation; Parallel and distributed computing; Parallel canonical differential evolutionary particle swarm optimization; GLOBAL OPTIMIZATION;
D O I
10.1016/j.ifacol.2018.11.692
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 proposes parallel canonical differential evolutionary particle swarm optimization (C-DEEPSO) for voltage and reactive power control (Volt Var Control: VVC). The problem can be formulated as a mixed integer nonlinear optimization problem (MINLP) and various evolutionary computation techniques have been applied to the problem including PSO, differential evolution (DE), and DEEPSO. Since VVC is one of the on-line controls, speed-up of computation is required. Moreover, there is still room for improvement on solution quality. This paper proposes parallel C-DEEPSO in order to speed up the calculation and improve solution quality and applies it to a VVC problem. The proposed method is applied to IEEE 118 bus system. The results indicate that the proposed method can realize fast computation and minimize active power losses more than conventional evolutionary computation techniques. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
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页码:143 / 148
页数:6
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