摘要
可再生能源增加了电力系统运行的不确定性,利用机会约束建立最优潮流模型来限制电力系统不确定性带来的风险,目前提出的计算方法通常假定不确定性的概率分布是已知的。提出一种基于数据驱动的分布式鲁棒机会约束最优潮流的算法:半正定规划,只需根据经验数据估计出不确定性的均值和方差。通过算例分析,验证了该分布式鲁棒最优潮流的性能优于高斯鲁棒最优潮流。
The renewable energy generation increases the uncertainty of power system operation.Optimal power flow model is established by using chance constraints to limit the risk caused by the power system uncertainty,which is an existing method to assume the known probability distribution of uncertainty.We propose a data-driven computing method for distributionally robust chance constrained optimal power flow based on semi-definite programming.This method only needed empirical data to estimate the mean and variance of uncertainty.The example analysis verifies that the proposed distributionally robust optimal power flow is better than that of the Gaussian robust optimal power flow.
作者
严雨豪
陈实
Yan Yuhao;Chen Shi(College of Electrical Engineering,Sichuan University,Chengdu 610065,Sichuan,China)
出处
《计算机应用与软件》
北大核心
2023年第11期93-99,共7页
Computer Applications and Software
关键词
电力系统
机会约束
半正定规划
不确定性
Power system
Chance constraint
Semi-definite programming
Uncertainty
