摘要
大规模分布式电源的并网给潮流计算中拉丁超立方抽样法的应用带来了新的问题。为解决分布式电源的累积分布函数较难获得以及相关性控制中相关系数矩阵非正定两个问题,提出了一种基于修正相关系数矩阵的改进拉丁超立方抽样法。该方法可根据离散数据,进行分层抽样得到样本,并采用正定谱分解法修正使得相关系数矩阵都能进行Cholesky分解,修正速度快误差小,毫秒级的速度便可使误差达到10-4。采用IEEE 33和PG＆E69两个节点系统,验证了修正算法的准确性和有效性。仿真结果表明该方法计算速度快,在采样与输出变量的准确性和收敛性方面都要优于蒙特卡罗。
The application of the Latin hypercube sampling method in the load flow calculation causes some new problems with the large-scale distributed generators connected to the distribution network. One is that the cumulative distribution function of distributed generators cannot be acquired easily; the other is that the correlation coefficient matrix is not positive-definite in correlation control. To solve these two problems, we proposed a new algorithm. The algorithm is based on the improved Latin hypercube sampling with modified correlation matrix. The algorithm stratifies sampling according to the discrete data and modifies the correlation coefficient matrix by positive definite spectral decomposition after which Cholesky decomposition can be applied to all recovered matrix. The speed of the algorithm is fast and the error can be less than 10-4. The accuracy and effectiveness of the proposed algorithm were proven by the comparative tests in the IEEE 33-bus system and PGE 69-bus system. The simulation results show that this method is faster, and the accuracy and convergence of the sampled and output variables are better than those of Monte Carlo.
作者
徐青山
杨阳
黄煜
刘建坤
卫鹏
XU Qingshan;YANG Yang;HUANG Yu;LIU Jiankun;WEI Peng(School of Electrical Engineering,Southeast University,Nanjing 210096,China;State Grid Jiangsu Electric Power Research Institute,Nanjing 211103,China)
出处
《高电压技术》
EI
CAS
CSCD
北大核心
2018年第7期2292-2299,共8页
High Voltage Engineering
基金
国家自然科学基金(51377021)
中央高校基本科研业务费专项资金(2242016K41064)
江苏省产学研前瞻项目(BY2016076-12)
国家电网公司科技项目(SGTYHT/14-JS-188)~~
关键词
光伏
随机潮流
相关性
非正定矩阵
CHOLESKY分解
拉丁超立方抽样
photovoltaic
probabilistic load flow
correlation
non-positive definite matrix
Cholesky decomposition
Latin hypercube sampling
