Dynamic reliability evaluation method of power grid security and stability control system based on Markov chain Monte Carlo

Abstract

The current reliability evaluation method of the security and stability control system (SSCS) is primarily based on static modeling, which fails to capture the dynamic aging and maintenance processes of individual devices within the system, thereby impacting the accuracy of evaluation results to a certain extent. Therefore, a dynamic reliability evaluation method of the SSCS based on Markov chain Monte Carlo (MCMC) is proposed in this paper. Firstly, the four-state non-homogeneous Markov model is constructed to simulate the aging process of the device, and the evaluation methods of each state are given. Secondly, according to the repair process, the influence of different maintenance strategies on the state transition of the device is analyzed to reflect the difference of state maintenance. Finally, the reliability of the SSCS is modeled dynamically by considering the temporal or conditional correlation of the state transition process of the security and stability control device. Taking the actual SSCS as an example, the reliability under different maintenance strategies is compared by simulation, and the sensitivity of model parameters is analyzed. The evaluation results show that this method can solve the time-varying availability of the SSCS, and can be used to guide the reasonable maintenance of the security and stability control device on site.

Keywords

• security and stability control system
• time-varying failure rate
• dynamic reliability
• condition-based maintenance
• markov chain monte carlo(mcmc)
• sensitivity