电力系统保护与控制Issue(22)：13-18,6.
基于TPNT和半不变量法的考虑输入量相关性概率潮流算法
A TPNT and cumulants based probabilistic load flow approach considering the correlation variables
摘要
Abstract
The correlation among input variables in power system affects the accuracy of probabilistic load flow (PLF) calculation. A PLF algorithm is proposed based on third-order polynomial normal transformation (TPNT) combining cumulants and Gram-Charlier expansion. The method that transforms a multivariate non-normal dependent random variables group into a multivariate standard normal independent one is used to calculate input variables and power flow based on correlation coefficient matrix and draw cumulative distribution curves of node status variables and load flow. The simulation results of the IEEE14-bus system with several correlative wind farms show that the proposed method is effective and accurate. <br> This work is supported by National High Technology Research and Development Program of China (863 Program) (No. 2011AA05112), National Natural Science Foundation of China (No. 51077042), Special Foundation of the Doctoral Program of Higher Education (No. 20120094110008), and Open Foundation of State Key Lab of Power System, Tsinghua University (No. SKLD11KZ02).关键词
风电并网/概率潮流/三阶多项式正态变换/半不变量/Gram-Charlier级数展开/输入量相关性Key words
wind power integration/probabilistic load flow/third-order polynomial normal transformation/cumulants/Gram-Charlier expansion/input variable correlation分类
信息技术与安全科学引用本文复制引用
刘小团,赵晋泉,罗卫华,赵军..基于TPNT和半不变量法的考虑输入量相关性概率潮流算法[J].电力系统保护与控制,2013,(22):13-18,6.基金项目
国家高技术研究发展计划项目（863计划）（2011AA05112）；国家自然科学基金项目(51077042)；高等学校博士学科点专项科研基金(20120094110008)；清华大学“电力系统及发电设备控制与仿真”国家重点实验室开放课题(SKLD11KZ02) （51077042）
