Probabilistic Load Flow Based on Mixed Copula and Uniform Design Sampling

doi:10.11930/j.issn.1004-9649.2016.02.109.05

Abstract

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

CLC Number:

TM712

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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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.2016.02.109.05

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

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