电力系统自动化2017，Vol.41Issue(7)：54-60,100,8.
基于广义多项式混沌法的含风电电力系统随机潮流
Probabilistic Load Flow for Wind Power Integrated System Based on Generalized Polynomial Chaos Methods
摘要
Abstract
The large-scale integration of wind power has increased the uncertainty in power systems.Probabilistic load flow calculation is a significant probabilistic analysis tool.Based on generalized polynomial chaos (gPC),a method is proposed to calculate probabilistic load flow with wind generation uncertainties.With this method,each random input variable is approximated by a finite-order expansion using optimal gPC basis functions.Then,a series of deterministic nonlinear equations can be built according to the orthogonality of gPC basis functions.Thus,the solution of random state variables' distribution is transformed into calculation of their gPC approximation coefficients.In addition,the idea of equivalent transformation is adopted to deal with the complexity of wind power probabilistic distribution and correction of wind speed.Calculation on an IEEE 30 bus system suggests that the proposed method can achieve a good degree of accuracy as well as higher computational efficiency in contrast to Monte Carlo simulation (MCS) method.关键词
随机潮流/风电场/相关性/等价变换/广义多项式混沌Key words
probabilistic load flow/wind farms/correlation/equivalent transformation/generalized polynomial chaos(gPC)引用本文复制引用
孙明,吴浩,邱一苇,龚建荣,宋永华..基于广义多项式混沌法的含风电电力系统随机潮流[J].电力系统自动化,2017,41(7):54-60,100,8.基金项目
国家自然科学基金资助项目(51377143) （51377143）
This work is supported by National Natural Science Foundation of China (No.51377143). （No.51377143）
