Reliability Evaluation of Virtual Power Plants Based on Bayesian Networks

JiachengHu, ZhangNing, Lingxiao Yang, CungangHu

Abstract: When utilizing traditional reliability analysis and evaluation methods to assess the reliability of virtual power plants, there are numerous shortcomings: the lack of intuitive representation of probabilistic relationships, difficulties in integrating and processing uncertain factors, leading to limited reasoning and fault diagnosis capabilities. To overcome these deficiencies, a reliability evaluation method for virtual power plants based on Bayesian network approaches is proposed. This method not only accurately calculates the reliability indices of virtual power plants but also visually demonstrates the extent of influence that individual components or combinations of components have on overall reliability. Firstly, a Bayesian network is employed to construct the reliability model of the virtual power plant. Secondly, the Bucket Elimination method is utilized for precise probability calculations. Finally, in conjunction with the Monte Carlo method, a comprehensive analysis of the reliability of the virtual power plant is conducted.

Submission Number: 15