Study on Capacitance Prediction of Power Capacitor Bank Based on Artificial Fish Swarm Algorithm

GE Wenhong; XU Jia; WANG Yuesheng; WANG Mingang; YAN Pingli; WU Jing

doi:10.14044/j.1674-1757.pcrpc.2018.03.003

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Study on Capacitance Prediction of Power Capacitor Bank Based on Artificial Fish Swarm Algorithm

更新时间：2024-09-14

- Study on Capacitance Prediction of Power Capacitor Bank Based on Artificial Fish Swarm Algorithm
- POWER CAPACITOR & REACTIVE POWER COMPENSATION Vol. 39, Issue 3, Pages: 11-15(2018)
- 作者机构：
  
  1. 国网淮北供电公司
  2. 国网安庆供电公司
- 作者简介：
- 基金信息：
- DOI：10.14044/j.1674-1757.pcrpc.2018.03.003
  CLC： TM53;TP18
- Published：2018，
- 稿件说明：
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[1]葛文红,徐佳,汪悦生,王明刚,颜平丽,吴静.基于鱼群算法优化ELM的电力电容器组电容量预测研究[J].电力电容器与无功补偿,2018,39(03):11-15+32.

GE WENHONG, XU JIA, WANG YUESHENG, et al. Study on Capacitance Prediction of Power Capacitor Bank Based on Artificial Fish Swarm Algorithm. [J]. Power capacitor & reactive power compensation, 2018, 39(3): 11-15.
[1]葛文红,徐佳,汪悦生,王明刚,颜平丽,吴静.基于鱼群算法优化ELM的电力电容器组电容量预测研究[J].电力电容器与无功补偿,2018,39(03):11-15+32. DOI： 10.14044/j.1674-1757.pcrpc.2018.03.003.

GE WENHONG, XU JIA, WANG YUESHENG, et al. Study on Capacitance Prediction of Power Capacitor Bank Based on Artificial Fish Swarm Algorithm. [J]. Power capacitor & reactive power compensation, 2018, 39(3): 11-15. DOI： 10.14044/j.1674-1757.pcrpc.2018.03.003.

摘要

为实现10 kV变电站电容器组电容量的准确预测

提高电容器的使用寿命和输变电系统的稳定性

文章提出一种基于AFSA优化ELM的权值和偏置的10 kV变电站电容器组电容量预测模型。该模型将AFSA算法应用于优化ELM的输入权值和隐含层偏置

实现ELM最优化预测。通过对PSO-ELM、GA-ELM和DE-ELM 3种方法的对比分析可知

AFSA-ELM进行10 kV变电站电容器组电容量预测具有预测精度高的优点

该方法可为电容器组电容预警提供决策依据和参考。

Abstract

For achieving accurate capacitance prediction of capacitor bank for 10 kV substation

improving the operation life of the capacitor and stability of the power transmission and transformation system

in this paper

a kind of capacitance prediction model of capacitor for 10 kV substation based on AFSA optimized ELM weight and offset is proposed.In this model

the AFSA algorithm is used to optimize input weight and hidden layer offset of ELM so to achieve ELM’s most optimization prediction.It is known through comparison and analysis of such three methods as PSO-ELM

GA-ELM and DE-ELM that capacitance prediction for capacitor of 10 kV substation with AFSA-ELM has the advantages of high prediction accuracy and the method and the method can provide decision base and reference for the capacitance prediction of capacitor bank.

关键词

鱼群算法（AFSA）极限学习机（ELM）遗传算法电容器差分进化算法

Keywords

artificial fish swarm algorithm（AFSA）extreme learning machine（ELM）genetic algorithmcapacitordifferential evolutionary algorithm

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