Multiobjective Optimization Applied to Maintenance Policy for Electrical Networks

Abstract

This paper propose an approach to multi-objective maintenance policy definition for electrical networks. Maximum asset performance is one of the major goals for electric power system managers. To reach this goal, minimal life cycle cost and maintenance optimization becomes crucial, while meeting demands from customers and regulators. This necessitates the determination of the optimal balance between preventive and corrective maintenance in order to obtain the lowest total cost. The approach of this paper is to study the problem of balance between preventive and corrective maintenance as a multiobjective optimization problem, where we have the customer interruptions on one hand and on the other hand the maintenance budget of the network operator. The problem is solved with meta-heuristics developed for the specific problem, as well as with an Evolutionary Particle Swarm Optimization algorithm. The maintenance optimization is applied in a case study to an urban distribution system in Stockholm, Sweden. Despite a general decreased level of maintenance (lower total maintenance cost) a better network performance can be given to the customers. This is achieved by focusing the preventive maintenance on components with a high potential for improvements. Beside this, the paper constitutes a display of the value in introducing more maintenance alternatives for every component and to choose the right level of maintenance for the components with respect to network performance.