Start-Up Optimisation of a Combined Cycle Power Plant with Multiobjective Evolutionary Algorithms

Abstract

In this paper we present a study of the application of Evolutionary Computation methods to the optimisation of the start-up of a combined cycle power plant. We propose a multiobjective approach considering different objectives for the optimisation in order to reduce the pollution emissions and to maximise the efficiency of the plant. We compare a multiobjective evolutionary algorithm (NSGA-II) with 2 and 5 objectives on a software simulator and then we use different metrics to measure the performances. We show that NSGA-II algorithm is able to provide a set of solutions, defined as Pareto Front, that represent the best trade-off on the different objectives among those the decision maker can choose.

Publication
Applications of Evolutionary Computation, pp. 151-160, Lecture Notes in Computer Science, https://doi.org/10.1007/978-3-642-12242-2_16
Date
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