A new solution for maintenance scheduling in deregulated environment applying Genetic Algorithm and Monte-Carlo Simulation

This paper presents a new comprehensive solution for maintenance scheduling of generating units in deregulated environments by applying an independent market, based on Genetic Algorithm (GA) and Monte-Carlo Simulation (MCS). In a deregulated environment each Generation Company (GENCO) desires to optimize the payoffs while independent system operator (ISO) has its reliability solicitudes. Mostly, these two points of view create many contests. Therefore, the paper proposes a competitive area based on GA for maintenance scheduling. In this method, GENCOs are set their strategies to participate in Maintenance Market (MM) by considering load and fuel uncertainties besides considering the behaviours of other companies. On the other hand, ISO manages the MM based on reliability and offers incentives/ penalties for companies relying on its policy through MCS. For disclosing the accuracy and the applicability of this mentioned solution for maintenance scheduling of power generation units, IEEE reliability test system (RTS) has been studied.