Coalitional model predictive control of parabolic-trough solar collector fields with population-dynamics assistance

Parabolic-trough solar collector fields are large-scale systems, so the application of centralized optimizationbased control methods to these systems is often not suitable for real-time control. As such, this paper formulates a novel coalitional control approach as an appropriate alternative to the...

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Detalhes bibliográficos
Autores: Sánchez Amores, Ana, Martínez Piazuelo, Juan Pablo, Maestre Torreblanca, José María, Ocampo-Martínez, Carlos|||0000-0001-9251-6044, Fernández Camacho, Eduardo, Quijano Silva, Nicanor
Formato: artículo
Fecha de publicación:2023
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/383015
Acesso em linha:https://hdl.handle.net/2117/383015
https://dx.doi.org/10.1016/j.apenergy.2023.120740
Access Level:acceso abierto
Palavra-chave:Solar thermal energy
Heat -- Transmission
Model predictive control
Coalitional control
Population dynamics
Distributed solar collector field
Energia tèrmica solar
Calor -- Transmissió
Àrees temàtiques de la UPC::Energies::Energia solar tèrmica
Descrição
Resumo:Parabolic-trough solar collector fields are large-scale systems, so the application of centralized optimizationbased control methods to these systems is often not suitable for real-time control. As such, this paper formulates a novel coalitional control approach as an appropriate alternative to the centralized scheme. The key idea is to split the overall solar collector field into smaller subsystems, each of them governed by a local controller. Then, controllers are clustered into coalitions to solve a local optimization-based problem related to the corresponding subset of subsystems, so that an approximate solution of the original centralized problem can be obtained in a decentralized fashion. However, the operational constraints of the solar collector field couple the optimization problems of the multiple coalitions, thus limiting the ability to solve them in a fully decentralized manner. To overcome this issue, a novel population-dynamics-assisted resource allocation strategy is proposed as a mechanism to decouple the local optimization problems of the multiple coalitions. The proposed coalitional methodology allows to solve the multiple local subproblems in parallel, hence reducing the overall computational burden, while guaranteeing the satisfaction of the operational constraints and without significantly compromising the overall performance. The effectiveness of proposed approach is shown through numerical simulations of a 10- and 100-loop version of the ACUREX solar collector field of Plataforma Solar de Almería, Spain.