Optimizing the start-up operations of combined cycle power plants using soft computing methods

Abstract

In this article we present a study on the application of soft computing methods for the start-up optimization of a combined cycle power plant. In particular, we use fuzzy sets in order to get a fitness function providing the effectiveness in the lattice 0, 1 of the given start-up regulations. Then we applied a genetic algorithm to find the best start-up regulations. Experimentation shows that the solution found remarkably improves the solution given by the process experts.

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