Application of meta-heuristic methods to generation expansion planning: advanced formulations and case studies

The generation expansion planning (GEP) is a very relevant optimization problem in power systems research. Several factors must be considered in the management of an optimal planning that aims at expanding the generation, such as satisfying a growing demand, dealing with costs of investment, operation and maintenance, dealing with pollutant emission, among others. Considering these aspects, this problem tends to be very complex and meta-heuristics methods have been employed in order to provide satisfactory solutions. This paper aims at reviewing GEP considering five different formulations of the problem and how meta-heuristics approaches can be applied to it. For this purpose, two case studies are presented and, in order to provide a deep analysis, these methods are compared according to their performance, the solution provided by them, and also comparing results obtained among different formulations, which leads to a promising methodology and some interesting results provided.

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