Home Energy Management Systems with Branch-and-Bound Model-Based Predictive Control Techniques
At a global level, buildings constitute one of the most significant energy-consuming sectors. Current energy policies in the EU and the U.S. emphasize that buildings, particularly those in the residential sector, should employ renewable energy and storage and efficiently control the total energy sys...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-09-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/14/18/5852 |
| _version_ | 1797519420669558784 |
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| author | Karol Bot Inoussa Laouali António Ruano Maria da Graça Ruano |
| author_facet | Karol Bot Inoussa Laouali António Ruano Maria da Graça Ruano |
| author_sort | Karol Bot |
| collection | DOAJ |
| description | At a global level, buildings constitute one of the most significant energy-consuming sectors. Current energy policies in the EU and the U.S. emphasize that buildings, particularly those in the residential sector, should employ renewable energy and storage and efficiently control the total energy system. In this work, we propose a Home Energy Management System (HEMS) by employing a Model-Based Predictive Control (MBPC) framework, implemented using a Branch-and-Bound (BAB) algorithm. We discuss the selection of different parameters, such as time-step, to employ prediction and control horizons and the effect of the weather in the system performance. We compare the economic performance of the proposed approach against a real PV-battery system existing in a household equipped with several IoT devices, concluding that savings larger than 30% can be obtained, whether on sunny or cloudy days. To the best of our knowledge, these are excellent values compared with existing solutions available in the literature. |
| first_indexed | 2024-03-10T07:42:32Z |
| format | Article |
| id | doaj.art-63d6bf77097344bb86b948c9e7fa46fe |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T07:42:32Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-63d6bf77097344bb86b948c9e7fa46fe2023-11-22T12:54:04ZengMDPI AGEnergies1996-10732021-09-011418585210.3390/en14185852Home Energy Management Systems with Branch-and-Bound Model-Based Predictive Control TechniquesKarol Bot0Inoussa Laouali1António Ruano2Maria da Graça Ruano3Faculty of Science & Technology, University of Algarve, 8005-294 Faro, PortugalFaculty of Science & Technology, University of Algarve, 8005-294 Faro, PortugalFaculty of Science & Technology, University of Algarve, 8005-294 Faro, PortugalFaculty of Science & Technology, University of Algarve, 8005-294 Faro, PortugalAt a global level, buildings constitute one of the most significant energy-consuming sectors. Current energy policies in the EU and the U.S. emphasize that buildings, particularly those in the residential sector, should employ renewable energy and storage and efficiently control the total energy system. In this work, we propose a Home Energy Management System (HEMS) by employing a Model-Based Predictive Control (MBPC) framework, implemented using a Branch-and-Bound (BAB) algorithm. We discuss the selection of different parameters, such as time-step, to employ prediction and control horizons and the effect of the weather in the system performance. We compare the economic performance of the proposed approach against a real PV-battery system existing in a household equipped with several IoT devices, concluding that savings larger than 30% can be obtained, whether on sunny or cloudy days. To the best of our knowledge, these are excellent values compared with existing solutions available in the literature.https://www.mdpi.com/1996-1073/14/18/5852home energy management systemsbuilding energymodel-based predictive controlbranch-and-bound algorithmsensitivity analysisphotovoltaics |
| spellingShingle | Karol Bot Inoussa Laouali António Ruano Maria da Graça Ruano Home Energy Management Systems with Branch-and-Bound Model-Based Predictive Control Techniques Energies home energy management systems building energy model-based predictive control branch-and-bound algorithm sensitivity analysis photovoltaics |
| title | Home Energy Management Systems with Branch-and-Bound Model-Based Predictive Control Techniques |
| title_full | Home Energy Management Systems with Branch-and-Bound Model-Based Predictive Control Techniques |
| title_fullStr | Home Energy Management Systems with Branch-and-Bound Model-Based Predictive Control Techniques |
| title_full_unstemmed | Home Energy Management Systems with Branch-and-Bound Model-Based Predictive Control Techniques |
| title_short | Home Energy Management Systems with Branch-and-Bound Model-Based Predictive Control Techniques |
| title_sort | home energy management systems with branch and bound model based predictive control techniques |
| topic | home energy management systems building energy model-based predictive control branch-and-bound algorithm sensitivity analysis photovoltaics |
| url | https://www.mdpi.com/1996-1073/14/18/5852 |
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