Multi objective Generation expansion planning in deregulated systems to consider benefit of generation company

This paper describes use of a new approach to solve multi-period multi-objective optimization of generation expansion planning problem in deregulated power systems over a long term planning horizon. Traditionally, the objective in undertaking aGeneration Expansion Planning (GEP) process has been tominimize the expected sum of yearly discounted costs(incorporate i.e., construction costs, operating costs, salvagevalue, etc.). Now, the objective is to apply GEP to today’scompetitive electricity markets in order to maximize the profitsof individual GENCOs (i.e., the revenues based on market pricesand capital and operating costs) and minimize emission of generation units objectives. This paper introduces a longtermexpansion model for GENCOs operating in the deregulatedelectricity environment. The model considers uncertainty,generation capacity limits, and expansion rate and investmentduring the expansion period.The proposed solution for multiobjective mathematical programming framework includes a hybrid augmented–weighted epsilon approach to obtain the Pareto optimal or efficient solutions for the problem. Finally, fuzzy decision making is implemented to select the most preferred solution among Pareto solutions based on the goals of decision makers