基于场景法的有源配电网动态无功优化  

Dynamic Reactive Power Optimization of Distribution Network with DGs Based on Scenario Method

作　　者：刘爱国[1] 沈一逸 侯显国 李渝鑫 李俊聪 金晨阳 LIU Aiguo;SHEN Yiyi;HOU Xianguo;LI Yuxin;LI Juncong;JIN Chenyang(School of Information Engineering,Nanchang University,Nanchang,Jiangxi 330031,China)

机构地区：[1]南昌大学信息工程学院,江西南昌330031

出　　处：《广东电力》2021年第9期18-26,共9页Guangdong Electric Power

摘　　要：随着分布式电源(distributed generation,DG)大量接入,配电网动态无功优化调度难度增加,现有方法存在不足,为此提出一种基于场景法的有源配电网动态无功优化方法。首先运用场景法描述DG出力的不确定性,采用Weibull分布和Beta分布分别构建风速和光照强度模型,通过DG出力公式,将随机问题转换为确定性问题;然后采用蒙特卡洛模拟法抽样和K均值聚类算法将样本聚类成3个典型场景,建立系统日内网损最小、无功补偿设备动作费用与变压器分接头调节代价费用最小为目标函数的多目标动态无功优化模型,并采用改进的多目标粒子群优化(multi-objective particle swarm optimization,MOPSO)算法对该优化模型进行求解;最后用所提方法对改进的IEEE 33节点系统进行仿真,验证其可行性。With a large number of distributed generation connected,the dynamic reactive power optimization scheduling of the distribution network has become more difficult,and the existing methods have shortcomings.For this reason,a scenario-based dynamic reactive power optimization method of the active distribution network is proposed.First,use the scene method to describe the uncertainty of DG output,use Weibull distribution and Beta distribution to build wind speed and light intensity models respectively,and use DG output formula to convert random problems into deterministic problems;then use Monte Carlo simulation method for sampling and K-means clustering algorithm clusters the samples into 3 typical scenarios,and establishes a multi-objective dynamic reactive power optimization model that minimizes the system’s intraday network loss,reactive power compensation equipment action costs and transformer tap adjustment costs as the objective function,and adopts improved The proposed multi-objective particle swarm optimization algorithm solves the optimization model;finally,the proposed method is used to simulate the improved IEEE 33-bus system to verify the feasibility.

关 键 词：分布式电源 场景分析 随机潮流 动态无功优化 

分 类 号：TM73[电气工程—电力系统及自动化]