A Simulated Annealing based approach to solve the generator maintenance scheduling problem

The scheduling of maintenance actions of generators is not a new problem but gained in recent years a new interest with the advent of electricity markets because inadequate schedules can have a significative impact on the revenues of generation companies. In this paper we report the research on this topic developed during the preparation of the MSc Thesis of the second author. The scheduling problem of generator maintenance actions is formulated as a mixed integer optimization problem in which we aim at minimizing the operation cost along the scheduling period plus a penalty on energy not supplied. This objective function is subjected to a number of constraints detailed in the paper and it includes binary variables to indicate that a generator is in maintenance in a given week. This optimisation problem was solved using Simulated Annealing. Simulated Annealing is a very appealing metaheuristic easily implemented and providing good results in numerous optimization problems. The paper includes results obtained for a Case Study based on a realistic generation system that includes 29 generation groups. This research work was proposed and developed with the collaboration of the third and fourth authors, from EDP Produção, Portugal.

Research highlights
► Mixed integer optimization model of the generator maintenance scheduling, GMS, problem.
► Consideration of a fictitious generator to represent energy not supplied.
► Penalization of the energy not supplied along the solution algorithm.
► Application of Simulated Annealing to the GMS problem.
► Application of the developed tool to a realistic generation system.