MOEA/D with Adaptive Mutation Operator Based on Walsh Decomposition: Application to Nuclear Reactor Control Optimization
Baptiste Gasse, Baptiste Gasse, Sébastien Verel, Jean-Michel Do
2023
Abstract
France has a fleet of nuclear reactors that makes up a significant proportion of the electricity generation mix. This over-representation of nuclear power compared with other energy sources leads reactors to operate in load following mode in order to balance supply and demand on the electricity grid. The increasing penetration of intermittent energies in the mix and the desire not to renew the entire current nuclear fleet bring active research into optimising the control of reactors operating in load following mode to allow them greater flexibility. In this study, we propose to solve a new bi-objective unit commitment problem using an MOEA/D algorithm equipped with an adaptive mutation operator based on a Walsh surrogate model of a black-box function with a high computation cost. The method consists of taking advantage of the linear effects associated with the problem variables thanks to the Walsh coefficients to regularly update the mutation rate of the variation operator and explore the problem’s search space more judiciously. We show that this method enables to penalize some variables by decreasing their mutation probability without affecting the global performance of the search for Pareto-optimal solutions, which makes it similar to an adaptive in-line fitness landscape analysis.
DownloadPaper Citation
in Harvard Style
Gasse B., Verel S. and Do J. (2023). MOEA/D with Adaptive Mutation Operator Based on Walsh Decomposition: Application to Nuclear Reactor Control Optimization. In Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: ECTA; ISBN 978-989-758-674-3, SciTePress, pages 75-85. DOI: 10.5220/0012177200003595
in Bibtex Style
@conference{ecta23,
author={Baptiste Gasse and Sébastien Verel and Jean-Michel Do},
title={MOEA/D with Adaptive Mutation Operator Based on Walsh Decomposition: Application to Nuclear Reactor Control Optimization},
booktitle={Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: ECTA},
year={2023},
pages={75-85},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012177200003595},
isbn={978-989-758-674-3},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: ECTA
TI - MOEA/D with Adaptive Mutation Operator Based on Walsh Decomposition: Application to Nuclear Reactor Control Optimization
SN - 978-989-758-674-3
AU - Gasse B.
AU - Verel S.
AU - Do J.
PY - 2023
SP - 75
EP - 85
DO - 10.5220/0012177200003595
PB - SciTePress