Start-Up optimisation of a combined cycle power plant with multiobjective evolutionary algorithms

Authors:
Ilaria Bertini;Matteo De Felice;Fabio Moretti;Stefano Pizzuti
Affiliations:
ENEA (Italian Energy New Technology and Environment Agency);ENEA (Italian Energy New Technology and Environment Agency);Dipartimento di Informatica e Automazione, Università degli Studi “Roma Tre”;ENEA (Italian Energy New Technology and Environment Agency)
Venue:
EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
Year:
2010

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Evolutionary Computation

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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.