Generation expansion planning in a competitive environment using a genetic algorithm

In this presentation, the authors propose a new framework for a generation expansion planning (GEP) applicable in a competitive environment using a genetic algorithm (GA). Unlike the traditional approaches, the new GEP in a competitive market is very complex due to conflicts among generation companies (GENCOs). The objective function of each GENCO for investment decision-making is to maximize its profit, while the objective of profit maximization of each GENCO is linked to others. Also, one of the objectives of the market regulatory body will be market stabilization through coordination between GENCOs by providing long-term market information to GENCOs, which can prevent extreme over/under investments in the electricity market. This presentation suggests a new solution algorithm that can deal with these conflicting objectives between GENCOs and the regulatory body using a genetic algorithm. Using a genetic algorithm solution scheme, the GEP problem for a competitive environment application can easily be solved.