基于扩展拉丁超立方采样的电力系统概率潮流计算

Probabilistic Load Flow Evaluation With Extended Latin Hypercube Sampling

概率潮流分析中,拉丁超立方采样(Latin hypercubesampling,LHS)算法比简单蒙特卡罗仿真(Monte Carlosimulation,MCS)的效率要高,但是传统LHS(conventionalLHS,CLHS)算法采样数必须事先确定并且固定。针对现有CLHS技术的不足,提出了扩展拉丁超立方采样算法(Extended LHS,ELHS)并应用于概率潮流计算。扩展方法根据已有的N点LHS采样构造2N点LHS采样并保证扩展前后的相关性相近,在增加采样数的同时保留已有的潮流计算结果。由于采样数无法事先确定,因此提出了以扩展前后估计值变化量的相对值作为ELHS的实用化收敛判据。采用MCS、CLHS和ELHS方法分别对IEEE 30节点和IEEE 118节点系统进行概率潮流分析,所提出的方法能够在保证计算精度的前提下获得ELHS在不同采样数下的收敛趋势。算例结果证明了所提方法的高效性、精确性和易扩展性。

For probabilistic load flow（PLF） analysis,Latin hypercube sampling（LHS） has higher efficiency than simple Monte Carlo simulation（MCS）.But sample size should be known in advance and fixed in conventional LHS（CLHS）.Due to these disadvantages of existing CLHS,extended LHS（ELHS） was proposed and applied in PLF analysis.Started with a LHS of sample size N and associated rank correlation,the extended procedure constructed a new LHS of sample size 2N.The new LHS contains the elements of the original LHS and has a rank correlation that is close to the original rank correlation.While increasing the sample size,the extended method retained the load flow results already obtained.Since the sample size could not be determined in advance,practical convergence criterion of ELHS was described by coefficient of variation ratio before and after the extension.PLF studies with MCS,CLHS,and ELHS were carried out on IEEE 30-bus and IEEE 118-bus test systems respectively.The proposed method could obtain convergence trend for ELHS at different sample sizes while the accuracy was maintained.The results verified the effectiveness,accuracy and expansibility of the proposed method.