A New Approach for Generator Maintenance Scheduling in Deregulated Power Systems

Abstract

This paper presents a parallel-refined simulated annealing (PRSA) approach for the generator maintenance scheduling (GMS) problem to maximize profit objective function. The merit of simulated annealing (SA) is preserved and the deficiency is pruned away in the proposed PRSA. The proposed PRSA is an effective method because the multiple search trajectories parallel and refined in each stage. The near optimal solution for each trajectory in current state can be derived from the local optimal solutions by using the parallel optimization process. The proposed parallel searching strategy can obtain optimal or near-optimal solution for the GMS problem. This paper has demonstrated the effectiveness and feasibility of applying the proposed approach for the 50-unit GMS problem.

Modelling generator maintenance scheduling costs in deregulated power markets

“…health insurance), test equipment, etc. Most formulations, however, concentrate only on total (fixed and variable) direct maintenance costs in the delivery of maintenance cost models [9,22,32]. A general model for scheduling maintenance is presented in [32], which uses maintenance costs of power generating units and the energy production cost within the objective function.…”

“…The model is a cost minimisation model which includes the direct maintenance cost. The maximisation of the profit objective function was considered by Chen et al [9] to find the best maintenance schedule for generators in deregulated power systems.…”

“…Regardless of the type of maintenance carried out, the generator units must be taken out of service for a period of time ranging from several hours to several weeks [13,32]. In the deregulated environment, the decision when to take the generator out of service depends on various factors such as the effect of maintenance outages on the overall system, reliability, loss of services, loss of firm's reputation and loss of revenue [9,10]. The coordination of this is usually done by the Independent System Operator (ISO).…”

An investigation into the effectiveness of simulated annealing as a solution approach for the generator maintenance scheduling problem

“…Although SA has been adopted a number of times in the GMS literature, we could find no reference to experimentation with respect to improving the SA algorithm's effectiveness in the GMS context -a single cooling schedule (geometric) and a single elementary neighbourhood move operator (a random unit's maintenance starting time is changed to a random new time) are utilised throughout the literature [1][2][3][4][5][6][7]. In this paper, three adaptive cooling schedules and a new compound neighbourhood move operator are introduced in the context of GMS and compared to the schedules currently suggested in the literature.…”