毛晓明,叶嘉俊,魏焕政,李牧星.基于Copula理论和切片采样技术结合拉丁超立方抽样的概率潮流计算[J].电测与仪表,2017,54(22):. MAO Xiaoming,YE Jiajun,WEI Huanzheng,LI Muxing.Probabilistic Load Flow Calculation Based on Copula Theory and Slice Sampling Technique Combined with Latin Hypercube Sampling[J].Electrical Measurement & Instrumentation,2017,54(22):.
基于Copula理论和切片采样技术结合拉丁超立方抽样的概率潮流计算
Probabilistic Load Flow Calculation Based on Copula Theory and Slice Sampling Technique Combined with Latin Hypercube Sampling
To assess the impact of large-scale new energy sources on the probabilistic power flow (PLF) of power systems, a Markov Chain Monte Carlo (MCMC) PLF method based on Copula theory, slice sampling and Latin hypercube sampling is proposed. The probabilistic model of the correlative input variables is established by the Copula theory with the Kendall rank correlation coefficient used to measure the correlations. The sample space of random input variables is obtained by slice sampling and the Latin hypercube sampling is further introduced to deal with the initial samples to improve efficiency. The modified IEEE 14-bus system is used as an example to demonstrate the correctness and effectiveness of the presented method and the influence of correlations between wind and photovoltaic power outputs on PLF is studied. The results show that wind and photovoltaic combined increases the reliability and economy of system operation and consideration of the correlations will provide a more accurate assessment on the effect of wind and photovoltaic outputs on PLF.
