Monte Carlo simulation model to coordinate the preventive maintenance scheduling of generating units in isolated distributed Power Systems

Abstract

The paper presents a risk-based model to coordinate the generators preventive maintenance of an isolated distributed Power System with wind generation presence. The model coordinates preventive maintenance minimizing the risk of loss of load probability in the Power System. The risk is estimated with a sequential Markov Chain Monte Carlo (MCMC) simulation model. In this paper, the preventive maintenance scheduling (PMS) of the generating units is a non-linear stochastic optimization problem and it is efficiently solved with the algorithms Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). The model allows Power System operators to obtain a maintenance schedule that minimizes the risk of loss of load probability, as much as possible in the Power System; as well as establishing the desired level of risk. The model is applied in a Cuban Power System isolated from the main national power grid constituting a distributed system, and has the presence of a wind farm in its energetic matrix. The paper demonstrates the proposed model effectiveness in this real Power System.