中圖分類號：TM71 文獻(xiàn)標(biāo)志碼：A DOI: 10.16157/j.issn.0258-7998.234202 中文引用格式： 郭子強(qiáng),，宋濤，郭杰,，等. 計(jì)及MCMC方法的電網(wǎng)概率檢修計(jì)劃指標(biāo)優(yōu)化模型[J]. 電子技術(shù)應(yīng)用,，2023，49(10)：15-22. 英文引用格式： Guo Ziqiang,，Song Tao,，Guo Jie，et al. Power grid probabilistic maintenance plan index optimization model with MCMC method[J]. Application of Electronic Technique,，2023,，49(10)：15-22.
Power grid probabilistic maintenance plan index optimization model with MCMC method
(Lanzhou Power Supply Company，State Grid Gansu Electric Power Company,，Lanzhou 730070,，China)
Abstract： Effective power maintenance schedule will significantly increase the reliability of power grid operation as a crucial component of assuring the normal operation of the power system. In order to achieve the optimization of the maintenance plan, a probabilistic maintenance model is created in this work using equipment condition categorization, equipment operation life, equipment operation cost, and other indicators. The Markov Chain Monte Carlo approach is utilized in the maintenance model to increase model accuracy, and the probabilistic maintenance plan optimization strategy is employed to improve the reliability and economic indicators of the power grid. Finally, simulation is used to assess and compare the probabilistic maintenance model and the conventional maintenance model. The superiority of the probabilistic maintenance model, which offers a theoretical foundation for the enhancement of the power maintenance link in the power industry value chain system, is highlighted while determining the best maintenance probability.
Key words : probabilistic maintenance；status classification,；reliability,；economic；Markov Chain Monte Carlo method
