电力工程技术2017，Vol.36Issue(1)：34-38,5.
基于半不变量和Gram－Charlier级数展开法的随机潮流算法
A Probabilistic Power Flow Algorithm Based on Semi-variable and Gram-Charlier Series Expansion
摘要
Abstract
With the growing scale of new energy, new energy power contribute often exhibit a strong correlation, traditional random flow algorithm for strong correlation random variables was considered less. A method of probabilistic power flow algorithm based on semi-variable and Gram-Charlier series expansion was proposed in this paper. According node voltage and branch current expectations and sensitivity matrix, with wind power output, load changes, forced outages and generator fault lines and other uncertainties considered, load and conventional generators, wind turbine output and each node injection power of each order half invariant were calculated. Probability density function and probability distribution function were obtained by Gram-Charlier series expansion. IEEE-30 node test shows that the algorithm can reflect the uncertainty of large-scale new energy accessing to the system, and probability density function can be simplified to the semi-invariant algebra. Greatly reduce the computation time and it has a good convergence.关键词
随机模型/半不变量/随机潮流/风电/Gram-Charlier级数Key words
stochastic model/semi-invariant/probabilistic power flow/wind power/Gram-Charlier series分类
信息技术与安全科学引用本文复制引用
卫鹏,刘建坤,周前,徐青山,黄煜..基于半不变量和Gram－Charlier级数展开法的随机潮流算法[J].电力工程技术,2017,36(1):34-38,5.基金项目
国家自然科学基金51577028；国家电网公司科技项目 （）
