CAJ | 학술논문

电力系统的不同输入量之间具有相关性，会影响概率潮流计算的准确性。提出基于三阶多项式正态变换方法处理随机变量相关性，结合半不变量与Gram-Charlier级数展开的概率潮流算法。该方法能够将相关非正态的多维随机变量变换到正态不相关的变量空间，得到相关系数矩阵处理相关输入量，然后进行概率潮流计算，得到节点状态变量和支路潮流功率的潮流计算结果和概率分布曲线。对含多个风速分布相关风电场的 IEEE14节点系统进行分析计算，结果验证了该方法的有效性和准确性。
전력계통적불동수입량지간구유상관성，회영향개솔조류계산적준학성。제출기우삼계다항식정태변환방법처리수궤변량상관성，결합반불변량여Gram-Charlier급수전개적개솔조류산법。해방법능구장상관비정태적다유수궤변량변환도정태불상관적변량공간，득도상관계수구진처리상관수입량，연후진행개솔조류계산，득도절점상태변량화지로조류공솔적조류계산결과화개솔분포곡선。대함다개풍속분포상관풍전장적 IEEE14절점계통진행분석계산，결과험증료해방법적유효성화준학성。
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).