基于混合Copula和均匀设计采样的电力系统随机潮流

doi:10.11930/j.issn.1004-9649.2016.02.109.05

摘要/Abstract

摘要： 为全面描述输入随机变量间的相关性并提高Monte Carlo模拟采样效率，提出一种基于混合Copula和均匀设计采样（uniform design sampling，UDS）的电力系统随机潮流计算方法。从输入随机变量的相关结构出发，构造混合Copula函数分析输入随机变量的相关性，准确描述输入随机变量间的非线性、非对称性以及尾部特征。运用均匀设计采样，克服传统Monte Carlo模拟采样规模过大、计算时间过长的缺点。以接风电场的IEEE30节点系统为例，进行仿真分析，与以实测数据进行仿真分析的结果进行对比，结果表明所提方法不仅速度快、精度高，而且能全面反映输入随机变量的相关性。

Abstract: In order to describe the dependency structure of the random input variables comprehensively and improve the sampling efficiency of Monte Carlo, a probabilistic load flow method based on mixed Copula and uniform design sampling is proposed in this paper. Firstly, Mixed Copula is constructed to analyze the correlation of the random input variables and describe the non-linear, asymmetric and tail characteristics. In traditional Monte Carlo simulation, the sampling scale is too large and the computation time is too long. To overcome the shortcomings, the uniform design sampling is used. The case study applies IEEE30-bus system with wind forms. The analyzing results show that the proposed method is fast in speed and high in precision. Furthermore, it can reflect the dependency structure of the random input variables comprehensively compared with the simulation results with the measured discrete data.

Key words: mixed Copula, correlativity, uniform design sampling, probabilistic load flow, Monte Carlo simulation

中图分类号:

TM712

周宜广，刘天琪. 基于混合Copula和均匀设计采样的电力系统随机潮流[J]. 中国电力, 2016, 49(2): 109-113.

ZHOU Yiguang, LIU Tianqi. Probabilistic Load Flow Based on Mixed Copula and Uniform Design Sampling[J]. Electric Power, 2016, 49(2): 109-113.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.2016.02.109.05

https://www.electricpower.com.cn/CN/Y2016/V49/I2/109

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