A Model For Electricity Generation Expansion Planning Problems

In this paper , a new mathematical model for the electricity generation expansion planning problem are presented. The model, in terms of planning, is among the long-term planning in their literature. However, the steps of model are on a monthly basis. Considering the soft and hard constraints together and fits with other features is the model concept in the real world. Classifying plants according to construction areas should be added to other model features. Then the exact solution to small - scale of the model is presented by the software (GAMS). Then, due to the complexity of the problem, two meta-heuristic algorithms, genetic and traininig – learninig based optimization, was presented. Genetic algorithm parameters are set using RSM. The 22 series of numerical examples by each of these two algorithms are solved and then the results were compared with each other. The results show that the genetic algorithm has the advantage.