Study on Reactive Power Optimization and Control Based on MFOA Algorithm

ZHANG Jie; ZHANG Qi; CHEN Jun

doi:10.14044/j.1674-1757.pcrpc.2017.05.003

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Study on Reactive Power Optimization and Control Based on MFOA Algorithm

更新时间：2024-09-14

- Study on Reactive Power Optimization and Control Based on MFOA Algorithm
- POWER CAPACITOR & REACTIVE POWER COMPENSATION Vol. 38, Issue 5, Pages: 12-16(2017)
- 作者机构：
  
  1. 宁波市大红鹰学院
  2. 吉林大学
- 作者简介：
- 基金信息：
- DOI：10.14044/j.1674-1757.pcrpc.2017.05.003
  CLC： TM714.3
- Published：2017，
- 稿件说明：
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[1]张杰,张琪,陈军.基于MFOA算法的无功优化和控制研究[J].电力电容器与无功补偿,2017,38(05):12-16.

ZHANG JIE, ZHANG QI, CHEN JUN. Study on Reactive Power Optimization and Control Based on MFOA Algorithm. [J]. Power capacitor & reactive power compensation, 2017, 38(5): 12-16.
[1]张杰,张琪,陈军.基于MFOA算法的无功优化和控制研究[J].电力电容器与无功补偿,2017,38(05):12-16. DOI： 10.14044/j.1674-1757.pcrpc.2017.05.003.

ZHANG JIE, ZHANG QI, CHEN JUN. Study on Reactive Power Optimization and Control Based on MFOA Algorithm. [J]. Power capacitor & reactive power compensation, 2017, 38(5): 12-16. DOI： 10.14044/j.1674-1757.pcrpc.2017.05.003.

摘要

为降低电力系统有功损耗

在果蝇优化算法的基础上

提出一种基于修正的果蝇优化算法的无功优化和控制算法研究。为了避免FOA算法陷入局部最优问题

将修正因子β引入基本的FOA算法

提出一种修正型的果蝇优化算法。以IEEE 30节点系统为研究对象

与FOA、PSO和内点法相比较可知

MFOA算法在潮流计算结果和收敛速度上均取得了较好的效果

优于FOA、PSO和内点法。

Abstract

For reducing the active power loss of power system

the reactive power optimization and controlalgorithm study based on a kind of corrected fruit fly optimization algorithm is proposed on the basis of thefruit fly optimization algorithm. For avoiding the partially most optimization issue which is caught by theFOA algorithm

the correction factor β is introduced into the basic FOA algorithm

and a kind ofcorrected type of fruit fly optimization algorithm is proposed. Taking the IEEE 30 node system as theresearch object

it is compared with FOA

PSO and interior point method that the MFOA algorithm hasbetter effect in both power flow calculation result and convergence speed

and it is superior than FOA

PSO and interior point method.

关键词

无功优化果蝇优化算法修正因子粒子群算法内点法

Keywords

reactive power optimizationfruit fly optimization algorithmcorrection factorparticle swarm algorithminterior point method

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