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Identification of a dynamic system model for a building and heating system including heat pump and thermal energy storage
Controllers employing optimal control strategies will path the way to enable flexible operations in future power grids. As buildings will increasingly act as prosumers in future power grids, optimal control of buildings’ energy consumption will play a major role in providing flexible operations. Opt...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7132096/ https://www.ncbi.nlm.nih.gov/pubmed/32274338 http://dx.doi.org/10.1016/j.mex.2020.100866 |
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author | Finck, Christian Li, Rongling Zeiler, Wim |
author_facet | Finck, Christian Li, Rongling Zeiler, Wim |
author_sort | Finck, Christian |
collection | PubMed |
description | Controllers employing optimal control strategies will path the way to enable flexible operations in future power grids. As buildings will increasingly act as prosumers in future power grids, optimal control of buildings’ energy consumption will play a major role in providing flexible operations. Optimal controllers such as model predictive controller are able to manage buildings’ operations and to optimise their energy consumption. For online optimisation, model predictive controller requires a model of the energy system. The more accurate the system model represents the system dynamics, the more accurate the model predictive controller predicts the future states of the energy system while optimising its energy consumption. In this article, we present a system model that can be used in online MPC, including dynamic programming as optimisation strategy. The system model is validated using a building and heating system, including heat pump and thermal energy storage. The following bullet points summarise the main requirements for the configuration of the system model: • The system model performs fast with low computational effort in less than 1 s; • The system model can be implemented in online MPC; • The system model accurately represents the dynamic behaviour. |
format | Online Article Text |
id | pubmed-7132096 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-71320962020-04-09 Identification of a dynamic system model for a building and heating system including heat pump and thermal energy storage Finck, Christian Li, Rongling Zeiler, Wim MethodsX Energy Controllers employing optimal control strategies will path the way to enable flexible operations in future power grids. As buildings will increasingly act as prosumers in future power grids, optimal control of buildings’ energy consumption will play a major role in providing flexible operations. Optimal controllers such as model predictive controller are able to manage buildings’ operations and to optimise their energy consumption. For online optimisation, model predictive controller requires a model of the energy system. The more accurate the system model represents the system dynamics, the more accurate the model predictive controller predicts the future states of the energy system while optimising its energy consumption. In this article, we present a system model that can be used in online MPC, including dynamic programming as optimisation strategy. The system model is validated using a building and heating system, including heat pump and thermal energy storage. The following bullet points summarise the main requirements for the configuration of the system model: • The system model performs fast with low computational effort in less than 1 s; • The system model can be implemented in online MPC; • The system model accurately represents the dynamic behaviour. Elsevier 2020-03-19 /pmc/articles/PMC7132096/ /pubmed/32274338 http://dx.doi.org/10.1016/j.mex.2020.100866 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Energy Finck, Christian Li, Rongling Zeiler, Wim Identification of a dynamic system model for a building and heating system including heat pump and thermal energy storage |
title | Identification of a dynamic system model for a building and heating system including heat pump and thermal energy storage |
title_full | Identification of a dynamic system model for a building and heating system including heat pump and thermal energy storage |
title_fullStr | Identification of a dynamic system model for a building and heating system including heat pump and thermal energy storage |
title_full_unstemmed | Identification of a dynamic system model for a building and heating system including heat pump and thermal energy storage |
title_short | Identification of a dynamic system model for a building and heating system including heat pump and thermal energy storage |
title_sort | identification of a dynamic system model for a building and heating system including heat pump and thermal energy storage |
topic | Energy |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7132096/ https://www.ncbi.nlm.nih.gov/pubmed/32274338 http://dx.doi.org/10.1016/j.mex.2020.100866 |
work_keys_str_mv | AT finckchristian identificationofadynamicsystemmodelforabuildingandheatingsystemincludingheatpumpandthermalenergystorage AT lirongling identificationofadynamicsystemmodelforabuildingandheatingsystemincludingheatpumpandthermalenergystorage AT zeilerwim identificationofadynamicsystemmodelforabuildingandheatingsystemincludingheatpumpandthermalenergystorage |