Market-based clustering of model predictive controllers for maximizing collected energy by parabolic-trough solar collector fields
| Autor: | Eva Masero Rubio, José María Maestre Torreblanca, Eduardo F. Camacho |
|---|---|
| Přispěvatelé: | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática |
| Rok vydání: | 2022 |
| Předmět: |
Market based
0209 industrial biotechnology Solar thermal applications Computer science business.industry 020209 energy Mechanical Engineering 02 engineering and technology Building and Construction Management Monitoring Policy and Law Thermal energy efficiency 020901 industrial engineering & automation General Energy Coalitional control Distributed solar collector field Concentrated solar power 0202 electrical engineering electronic engineering information engineering Parabolic trough Aerospace engineering Nonlinear model predictive control business Cluster analysis Energy (signal processing) |
| Zdroj: | Applied Energy idUS. Depósito de Investigación de la Universidad de Sevilla instname |
| ISSN: | 0306-2619 |
| DOI: | 10.1016/j.apenergy.2021.117936 |
| Popis: | This article focuses on maximizing the thermal energy collected by parabolic-trough solar collector fields to increase the production of the plant. To this end, we propose a market-based clustering model predictive control strategy in which controllers of collector loops may offer and demand heat transfer fluid in a market. When a transaction is made between loop controllers, a coalition is formed, and the corresponding agents act as a single entity. The proposed hierarchical algorithm fosters the formation of coalitions dynamically to improve the overall control objective, increasing the thermal energy delivered by the field. Finally, the proposed controller is assessed via simulation with other control methods in two solar parabolic-trough fields. The results show that the energy efficiency with the clustering strategy outperforms by % that of traditional controllers, and the method is implementable in real-time to control large-scale solar collector fields, where significant gains in thermal collected energy can be obtained, due to its scalability. |
| Databáze: | OpenAIRE |
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