电力系统保护与控制Issue(20)：13-19,7.
基于Copula理论的计及输入随机变量相关性的概率潮流计算
Probabilistic load flow considering correlation between input random variables based on Copula theory
摘要
Abstract
It is of great significance to consider uncertainty factors and correlation factors in order to assess load flow characteristics of power system accurately and comprehensively. Copula theory is introduced to establish the probability distribution model of correlated input random variables. A method to obtain input random variable’s empirical cumulative distribution function and inverse function based on measured discrete data is proposed to handle the input random variable whose marginal distribution doesn’t follow common distribution function. Copula theory is applied into Monte Carlo simulation method, and a probabilistic load flow (PLF) method which can deal with the correlation between input random variables flexibly is proposed. Taking wind power for example, the accuracy of probability distribution model of correlated input random variables established by Copula theory is evaluated. The validity of proposed PLF method is tested on the IEEE 57 bus system with wind power. The simulation results show that the proposed method is effective and accurate.关键词
概率潮流/Copula理论/相关性/蒙特卡罗仿真法/风电场出力Key words
probabilistic load flow/Copula theory/correlation/Monte Carlo simulation method/wind farm power output分类
信息技术与安全科学引用本文复制引用
蔡德福,石东源,陈金富..基于Copula理论的计及输入随机变量相关性的概率潮流计算[J].电力系统保护与控制,2013,(20):13-19,7.基金项目
国家重点基础研究发展计划项目(973项目)(2009CB219701)；国家863高技术基金项目(2011AA05A101，2011AA05A109)；国家自然科学基金项目(50937002)；南方电网公司科技项目(CSG[2013]0301ZD1)基金项目国家重点基础研究发展计划项目(973项目)(2009CB219701)；国家863高技术基金项目(2011AA05A101，2011AA05A109)；国家自然科学基金项目(50937002)；南方电网公司科技项目(CSG[2013]0301ZD1)@@@@This work is supported by National Basic Research Program of China (973 Program)(No.2009CB219701), National High-tech R&D Program of China (863 Program)(No.2011AA05A101, No.2011AA05A109), National Natural Science Foundation of China (No.50937002), National Natural Science Foundation of China (No.50937002), and Science and Technology Project of China Southern Power Grid (No. CSG[2013]0301ZD1) （973项目）
