Matheuristics to optimize refueling and maintenance planning of nuclear power plants
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Matheuristics to optimize refueling and maintenance planning of nuclear power plants Nicolas Dupin1
· El-Ghazali Talbi2
Received: 13 December 2018 / Revised: 13 May 2020 / Accepted: 16 July 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Planning the maintenance of nuclear power plants is a complex optimization problem, involving a joint optimization of maintenance dates, fuel constraints and power production decisions. This paper investigates Mixed Integer Linear Programming (MILP) matheuristics for this problem, to tackle large size instances used in operations with a time scope of 5 years, and few restrictions with time window constraints for the latest maintenance operations. Several constructive matheuristics and a Variable Neighborhood Descent local search are designed. The matheuristics are shown to be accurately effective for medium and large size instances. The matheuristics give also results on the design of MILP formulations and neighborhoods for the problem. Contributions for the operational applications are also discussed. It is shown that the restriction of time windows, which was used to ease computations, induces large over-costs and that this restriction is not required anymore with the capabilities of matheuristics or local searches to solve such size of instances. Our matheuristics can be extended to a biobjective optimization extension with stability costs, for the monthly re-optimization of the maintenance planning in the real-life application. Keywords Hybrid heuristics · Matheuristics · Mixed integer programming · Maintenance planning · Nuclear power plants · Optimization in energy
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Nicolas Dupin [email protected] El-Ghazali Talbi [email protected]
1
Université Paris-Saclay, CNRS, Laboratoire de recherche en informatique, 91405 Orsay, France
2
CNRS UMR 9189 - CRIStAL - Centre de Recherche en Informatique Signal et Automatique de Lille, Univ. Lille, 59000 Lille, France
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N. Dupin and E.-G. Talbi
1 Introduction Planning maintenance of nuclear power plants is a crucial issue in energy management, with huge financial stakes in France (Renaud 1993). Indeed, the part of nuclear production in the French power production is around 60–70%, and the marginal costs of nuclear production are lower than the ones of other thermal power plants (Khemmoudj 2007). At a first glance, the nuclear power plants should be in maintenance when the demands in electricity are low, especially in summer. Technical and operational constraints must be satisfied for the maintenance planning, it makes difficult to plan the maintenance for human experts. Operations research approaches were investigated since the 70’s (Dopazo and Merrill 1975). With the continuous progress of hardware and algorithms, especially in Mixed Integer Linear Programming (MILP), it became possible to tackle more complex and realistic problems in the decision support (Fourcade et al. 1997). The sizes of the real-life instances has always been a challenging issue. Heur
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