电力系统自动化2026，Vol.50Issue(4)：101-110,10.DOI:10.7500/AEPS20250512010
基于双稀疏化多项式混沌展开的高维配电网风险评估方法
High-dimensional Risk Assessment Method for Distribution Network Based on Dual-sparse Polynomial Chaos Expansion
摘要
Abstract
At present,with the high penetration of renewable energy grid-connection and the increasing fluctuation of loads,the challenge of uncertainty in distribution network operation is becoming more severe.How to achieve accurate and efficient risk assessment in complex high-dimensional scenarios has become an urgent key problem.To address this,this paper proposes a polynomial chaos expansion(PCE)method with dual sparsification to rapidly evaluate the operation risk of distribution networks under the influence of uncertain factors such as renewable energy output fluctuations.First,at the basis-function level,the hyperbolic truncation and least absolute shrinkage and selection operator(Lasso)regression are used to sparsify the basis functions,which significantly alleviates the exponential growth of the number of basis functions with polynomial order in traditional PCE.Then,at the collocation-point level,the Clenshaw-Curtis quadrature rule and the Smolyak sparse grid are applied to sparsify the collocation points,which effectively reduces the computational complexity while maintaining model accuracy.Finally,the simulation results on the IEEE 33-bus,IEEE 118-bus,and 322-bus distribution systems show that,compared with traditional PCE method,the proposed method significantly improves computational efficiency while maintaining result accuracy.关键词
配电网/风险评估/多项式混沌展开/基函数/稀疏化/配置点Key words
distribution network/risk assessment/polynomial chaos expansion/basis function/sparsification/collocation point引用本文复制引用
黄煜,李忠行,岳东,胡松林,王毅,谈超..基于双稀疏化多项式混沌展开的高维配电网风险评估方法[J].电力系统自动化,2026,50(4):101-110,10.基金项目
江苏省自然科学基金资助项目(BK20232026). This work is supported by Jiangsu Provincial Natural Science Foundation of China(No.BK20232026). （BK20232026）
