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.

• Type: Conference
• Year: 2010
• Where: EVOW
• Authors: Ilaria Bertini, Matteo De Felice, Fabio Moretti, Stefano Pizzuti
• Keywords: Artificial Intelligence, Combined Cycle Power Plant, Different Objectives, EVOW 2010, Multiobjective Evolutionary Algorithm