Data Driven Optimization of Energy Management in Residential Buildings with Energy Harvesting and Storage
This paper presents a battery-aware stochastic control framework for residential energy management systems (EMS) equipped with energy harvesting, that is, photovoltaic panels, and storage capabilities. The model and control rationale takes into account the dynamics of load, the weather, the weather...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/9/2201 |
| _version_ | 1827717561711591424 |
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| author | Nadia Ahmed Marco Levorato Roberto Valentini Guann-Pyng Li |
| author_facet | Nadia Ahmed Marco Levorato Roberto Valentini Guann-Pyng Li |
| author_sort | Nadia Ahmed |
| collection | DOAJ |
| description | This paper presents a battery-aware stochastic control framework for residential energy management systems (EMS) equipped with energy harvesting, that is, photovoltaic panels, and storage capabilities. The model and control rationale takes into account the dynamics of load, the weather, the weather forecast, the utility, and consumer preferences into a unified Markov decision process. The embedded optimization problem is formulated to determine the proportion of energy drawn from the battery and the grid to minimize a cost function capturing a user-defined tradeoff between battery degradation and financial expense by user preferences. Numerical results are based on real-world weather data for Golden, Colorado, and load traces. The results illustrate the ability of the system to limit battery degradation assessed using the Rain flow counting method for lithium ion batteries. |
| first_indexed | 2024-03-10T20:05:10Z |
| format | Article |
| id | doaj.art-2402de70a95f47f5ae11971ad955cab7 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T20:05:10Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-2402de70a95f47f5ae11971ad955cab72023-11-19T23:19:46ZengMDPI AGEnergies1996-10732020-05-01139220110.3390/en13092201Data Driven Optimization of Energy Management in Residential Buildings with Energy Harvesting and StorageNadia Ahmed0Marco Levorato1Roberto Valentini2Guann-Pyng Li3Donald Bren School of Information and Computer Science, University of California, Irvine, CA 92697, USADonald Bren School of Information and Computer Science, University of California, Irvine, CA 92697, USADepartment of Information Engineering, Computer Science and Mathematics, University of L’Aquila, 67100 L’Aquila, ItalyDonald Bren School of Information and Computer Science, University of California, Irvine, CA 92697, USAThis paper presents a battery-aware stochastic control framework for residential energy management systems (EMS) equipped with energy harvesting, that is, photovoltaic panels, and storage capabilities. The model and control rationale takes into account the dynamics of load, the weather, the weather forecast, the utility, and consumer preferences into a unified Markov decision process. The embedded optimization problem is formulated to determine the proportion of energy drawn from the battery and the grid to minimize a cost function capturing a user-defined tradeoff between battery degradation and financial expense by user preferences. Numerical results are based on real-world weather data for Golden, Colorado, and load traces. The results illustrate the ability of the system to limit battery degradation assessed using the Rain flow counting method for lithium ion batteries.https://www.mdpi.com/1996-1073/13/9/2201residential demand responseenergy management systemstochastic controlbattery agingmarkov decision processes |
| spellingShingle | Nadia Ahmed Marco Levorato Roberto Valentini Guann-Pyng Li Data Driven Optimization of Energy Management in Residential Buildings with Energy Harvesting and Storage Energies residential demand response energy management system stochastic control battery aging markov decision processes |
| title | Data Driven Optimization of Energy Management in Residential Buildings with Energy Harvesting and Storage |
| title_full | Data Driven Optimization of Energy Management in Residential Buildings with Energy Harvesting and Storage |
| title_fullStr | Data Driven Optimization of Energy Management in Residential Buildings with Energy Harvesting and Storage |
| title_full_unstemmed | Data Driven Optimization of Energy Management in Residential Buildings with Energy Harvesting and Storage |
| title_short | Data Driven Optimization of Energy Management in Residential Buildings with Energy Harvesting and Storage |
| title_sort | data driven optimization of energy management in residential buildings with energy harvesting and storage |
| topic | residential demand response energy management system stochastic control battery aging markov decision processes |
| url | https://www.mdpi.com/1996-1073/13/9/2201 |
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