Application of particle swarm optimization for an optimal maintenance strategy in transmission systems

Abstract

This paper presents the application of particle swarm optimization (PSO) technique to find the optimal maintenance strategy of transmission equipment with minimum total expected cost of generation cost, maintenance cost, repair cost and outage cost. Three types of transmission equipment, the overhead line, the underground cable and the insulator are considered. To consider aging, the equipment state model through modified Markov chain is proposed. Simulation is performed on IEEE 9-bus systems. The results obtained are quite encouraging and will be useful in maintenance scheduling.

Lifetime efficiency index model for optimal maintenance of power substation equipment based on cuckoo optimisation algorithm

“…In this process, the failure rate function is increasing with time or operation for β > 1, decreasing for β < 1 and constant when β = 1. Hence, it can be modelled by reliability measurement from the Weibull distribution where beta is more than one (β > 1) as presented in (10). A common special case that is used in this paper is named as the Rayleigh distribution (β = 2).…”

“…Many studies have discussed maintenance [5][6][7][8][9][10][11][12]. Some paper analysed it from aspects of maintenance policy optimisation and maintenance planning [5][6][7][8].…”

“…For instance, in [9] the optimal PM problem for substation components is solved by a Monte Carlo simulation technique, but most studies are focused on solving the optimal maintenance problem by particle swarm optimisation (PSO) or genetic algorithm (GA) techniques. For instance, [10] is about the application of PSO for the optimum maintenance in transmission systems and [11] is about finding the optimum scheduling for maintenance period by hybrid scatter-genetic algorithm (HS-GA), while [12] presented a method for reliability centered maintenance (RCM) programs by a multi-objective GA. Several papers presented new methods and models for solving maintenance problem and modelling components condition. For instance, [13] presented a new method named T* strategy to find the optimal maintenance time and [14] presented a new model for reliability analysis.…”