Minimizing the standard deviation of the thermal load in the spent nuclear fuel cask loading problem
The paper assumes that, at the end of the operational period of a Spanish nuclear power plant, an Independent Spent Fuel Storage Installation will be used for long-term storage. Spent fuel assemblies are selected and transferred to casks for dry storage, with a series of imposed restrictions (e.g.,...
| Autores: | , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/334748 |
| Acceso en línea: | https://hdl.handle.net/2117/334748 https://dx.doi.org/10.3390/en13184869 |
| Access Level: | acceso abierto |
| Palabra clave: | Spent reactor fuels Mixed integer linear programming (MILP) Multi-start metaheuristics Spent nuclear fuel Nuclear power plant operations Independent Spent Fuel Storage Installation (ISFSI) Combustibles nuclears gastats Àrees temàtiques de la UPC::Física |
| Sumario: | The paper assumes that, at the end of the operational period of a Spanish nuclear power plant, an Independent Spent Fuel Storage Installation will be used for long-term storage. Spent fuel assemblies are selected and transferred to casks for dry storage, with a series of imposed restrictions (e.g., limiting the thermal load). In this context, we present a variant of the problem of spent nuclear fuel cask loading in one stage (i.e., the fuel is completely transferred from the spent fuel pool to the casks at once), offering a multi-start metaheuristic of three phases. (1) A mixed integer linear programming (MILP-1) model is used to minimize the cost of the casks required. (2) A deterministic algorithm (A1) assigns the spent fuel assemblies to a specific region of a specific cask based on an MILP-1 solution. (3) Starting from the A1 solutions, a local search algorithm (A2) minimizes the standard deviation of the thermal load among casks. Instances with 1200 fuel assemblies (and six intervals for the decay heat) are optimally solved by MILP-1 plus A1 in less than one second. Additionally, A2 gets a Pearson’s coefficient of variation lower than 0.75% in less than 260s CPU (1000 iterations) |
|---|