今日自动化2024，Issue(11) ：143-144,150.

基于优化粒子群算法和分布式电源配置模型的电能质量研究

Research on Power Quality Based on Optimized Particle Swarm Optimization Algorithm and Distributed Power Supply Configuration Model

李晓峰
今日自动化2024，Issue(11) ：143-144,150.
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  • 维普
  • 万方数据

基于优化粒子群算法和分布式电源配置模型的电能质量研究

Research on Power Quality Based on Optimized Particle Swarm Optimization Algorithm and Distributed Power Supply Configuration Model

李晓峰1
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作者信息

  • 1. 国网河北省电力有限公司宁晋县供电分公司,河北 邢台 055550
  • 折叠

摘要

电力系统中分布式柔性资源不确定性强,数量众多,为电力系统的电能质量带来了挑战.研究采用机器学习算法智能配置分布式电源的并网策略,以提高系统的电能质量.对基本粒子群算法进行随机变异改进,建立了基于改进粒子群算法的分布式电源优化配置模型.仿真试验结果表明,该模型可有效提高分布式电源并网后的电力系统电能质量.

Abstract

Distributed flexible resources are uncertain and abundant in power system,which brings challenges to power quality of power system.In order to improve the power quality of the system,the network access strategy of distributed power supply intelligently configured by machine learning algorithm is studied.Based on the improved particle swarm optimization algorithm(PSO),a distributed power supply optimization model was established.The simulation results show that the model can effectively improve the power quality of the power system after the distributed power supply is connected to the network.

关键词

电压质量/分布式/优化配置/风力/光伏

Key words

voltage quality/distributed/optimization/wind power/photovoltaic

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出版年

2024
今日自动化

今日自动化

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