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OA

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.