摘要
为准确分析新能源渗透率不断加大的现代电力系统的运行特点,在传统概率潮流(PLF)计算过程中引入Copula理论来处理输入变量之间的相关性.针对传统PLF计算方法计算过程复杂、较难收敛的弊端,采用低偏差序列实现高效采样,加快算法收敛速度,提出一种Copula理论与准蒙特卡洛相结合的PLF计算方法.该方法首先采用准蒙特卡洛对输入变量的概率密度函数实现均匀、高效采样,然后通过Copula理论实现指定相关性向所得低偏差样本的转移.在IEEE-14和IEEE-30节点系统分别进行PLF计算和最优潮流计算验证算法的有效性.仿真结果表明:本文所提方法相较于传统PLF计算方法可准确描述变量之间的相关性,且具有快速收敛的优点.
In order to accurately analyze the operation characteristics of modern power system with increasing new energy permeability, the traditional probability power flow(PLF) calculation process introduces Copula theory to deal with the correlation between input variables. Aiming at the disadvantages of the traditional PLF calculation method such as complicated calculation process and difficult convergence, the low-deviation sequence is adopted to realize efficient sampling and accelerate the convergence speed of the algorithm;and a PLF calculation method combining Copula theory and Quasi-Monte Carlo is proposed. In this method, the probability density function of input variables are sampled uniformly and efficiently by Quasi-Monte Carlo method, and then the designated correlation is transferred to the low-deviation samples by Copula theory. The validity of the algorithm is verified by PLF calculation and optimal power flow calculation respectively for IEEE-14 and IEEE-30 node systems. Simulation results show that the method proposed can accurately describe the correlation between variables;and it has the advantages of rapid convergence compared with the traditional PLF calculation method.
作者
董晓阳
苏宏升
罗世昌
Dong Xiaoyang;Su Hongsheng;Luo Shichang(College of Automation & Electrical Engineering,Lanzhou Jiaotong Univ.,Lanzhou 730070,China)
出处
《三峡大学学报（自然科学版）》
CAS
北大核心
2019年第5期90-95,共6页
Journal of China Three Gorges University：Natural Sciences
基金
国家自然科学基金青年基金项目(61867003)
关键词
概率潮流
概率最优潮流
COPULA理论
准蒙特卡洛
相关系数
probabilistic power flow
probabilistic optimal power flow
Copula theory
quasi monte carlo
correlation coefficient
