Probabilistic Voltage Stability Evaluation Algorithm Based on Mixed Vine Copula and ILHS

Abstract

Abstract: In order to evaluate the impact of solar and photovoltaic output with complex correlation on power system voltage stability, a probabilistic voltage stability evaluation (PVSE) algorithm based on mixed vine Copula and inherit Latin hypercube sampling (ILHS) is proposed. Based on fuzzy c-means clustering, the scenarios of wind speed and solar radiation data in the practical power grid is divided. The AD distance is used to evaluate the optimal vine structure in different scenarios, and a probability input model based on mixed vine Copula is established. The sample points are sampled from the probability input model by using the ILHS, and the number of sample points is gradually increased according to the convergence criterion until PVSE converges. At the same time, the previously generated sample points and their corresponding results are continuously reused in the process of probability analysis, so as to greatly improve the efficiency of probability analysis. Based on the IEEE-118 bus system, the effectiveness of the proposed algorithm is verified. The results show that the proposed algorithm can accurately describe the correlation structure of multi-dimensional input data, and the calculation accuracy and speed of PVSE can be greatly improved by using the proposed algorithm.

Key words: Copula function, mixed vine, latin hypercube sampling, voltage stability evaluation; , correlation

PENG Sui, XU Liang, ZHANG Zhi-qiang, LOU Yuan-yuan, YU Hao, QIN Xiao-hui. Probabilistic Voltage Stability Evaluation Algorithm Based on Mixed Vine Copula and ILHS[J]. Computer and Modernization, 2022, 0(12): 6-12.

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