摘要
Abstract
With the large-scale integration of new energy sources,the distribution network becomes increasingly complex and variable.In order to deal with the reactive power problem caused by the high proportion of renewable energy connected to the distribution net-work,it proposes a reactive power optimization scheduling model based on the improved particle swarm optimization(PSO)algorithm.This model aims to optimize the operating cost of multi-energy systems,reduce network losses.Through reactive power compensation,energy storage regulation and energy conversion,it ensures the economy and operation safety of the power grid.Firstly,it improves the traditional PSO algorithm,applies chaotic initialization in conjunction with a reverse learning strategy to generate the initial popula-tion,optimizing it to accelerate convergence.Secondly,it uses nonlinear strategies and a golden sine algorithm search strategy to en-hance the inertia weight formula,learning factors,and position update formulas,thereby improving the search efficiency of the algo-rithm.Finally,the traditional PSO algorithm and the improved PSO algorithm are applied to simulation comparisons on the IEEE 33-node system.The simulation result verifies the effectiveness of the improvements.关键词
配电网/无功优化/改进粒子群算法Key words
distribution network/reactive power optimization/improved particle swarm algorithm分类
动力与电气工程
