电力系统自动化2025，Vol.49Issue(6)：157-164,8.DOI:10.7500/AEPS20230516007
基于样本弱依赖多项式混沌展开式的电网小干扰概率分析
Small-signal Probabilistic Analysis for Power Grids Based on Low-sample-dependent Polynomial Chaos Expansion
摘要
Abstract
With the high penetration rate of photovoltaics and other new energy resources,probabilistic analysis is essential due to the gradually increasing randomness of power grids.The methods such as polynomial chaos expansion can obtain the accurate results of probabilistic analysis,but the sample demand and the calculation cost increase exponentially with the increasing number of random variables.To solve this problem,a small-signal probabilistic analysis method for power grids based on low-sample-dependent polynomial chaos expansion is proposed.This method constructs a small number of simulation samples based on the tensor completion model,and the tensor completion algorithm based on improved generative adversarial network is used to extract the distribution characteristics of existing samples and expand the number of samples,so as to reduce the dependence of polynomial chaos expansion on the number of samples.The effectiveness of the proposed method is verified by simulation.The results show that the number of samples can be greatly reduced while ensuring the accuracy of analysis results with the proposed method.关键词
概率分析/小干扰/稳定性/多项式混沌展开式/张量补全/生成对抗网络Key words
probabilistic analysis/small-signal/stability/polynomial chaos expansion/tensor completion/generative adversarial network引用本文复制引用
齐宗强,窦晓波,卜强生,吕朋蓬,徐晓春..基于样本弱依赖多项式混沌展开式的电网小干扰概率分析[J].电力系统自动化,2025,49(6):157-164,8.基金项目
国家电网公司科技项目(5108-202218280A-2-367-XG). This work is supported by State Grid Corporation of China(No.5108-202218280A-2-367-XG). （5108-202218280A-2-367-XG）
