Assessment of Solar Energy Generation Toward Net-Zero Energy Buildings
With the continuous rise in the energy consumption of buildings, the study and integration of net-zero energy buildings (NZEBs) are essential for mitigating the harmful effects associated with this trend. However, developing an energy management system for such buildings is challenging due to uncert...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/17/11/528 |
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| author | Rayan Khalil Guilherme Vieira Hollweg Akhtar Hussain Wencong Su Van-Hai Bui |
| author_facet | Rayan Khalil Guilherme Vieira Hollweg Akhtar Hussain Wencong Su Van-Hai Bui |
| author_sort | Rayan Khalil |
| collection | DOAJ |
| description | With the continuous rise in the energy consumption of buildings, the study and integration of net-zero energy buildings (NZEBs) are essential for mitigating the harmful effects associated with this trend. However, developing an energy management system for such buildings is challenging due to uncertainties surrounding NZEBs. This paper introduces an optimization framework comprising two major stages: (i) renewable energy prediction and (ii) multi-objective optimization. A prediction model is developed to accurately forecast photovoltaic (PV) system output, while a multi-objective optimization model is designed to identify the most efficient ways to produce cooling, heating, and electricity at minimal operational costs. These two stages not only help mitigate uncertainties in NZEBs but also reduce dependence on imported power from the utility grid. Finally, to facilitate the deployment of the proposed framework, a graphical user interface (GUI) has been developed, providing a user-friendly environment for building operators to determine optimal scheduling and oversee the entire system. |
| format | Article |
| id | doaj-art-1f7e673ac92445ecb88da4f28cf021c2 |
| institution | Kabale University |
| issn | 1999-4893 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj-art-1f7e673ac92445ecb88da4f28cf021c22024-11-26T17:45:31ZengMDPI AGAlgorithms1999-48932024-11-01171152810.3390/a17110528Assessment of Solar Energy Generation Toward Net-Zero Energy BuildingsRayan Khalil0Guilherme Vieira Hollweg1Akhtar Hussain2Wencong Su3Van-Hai Bui4Department of Electrical and Computer Engineering, University of Michigan—Dearborn, Dearborn, MI 48128, USADepartment of Electrical and Computer Engineering, University of Michigan—Dearborn, Dearborn, MI 48128, USADepartment of Electrical and Computer Engineering, Laval University, Quebec, QC G1V 0A6, CanadaDepartment of Electrical and Computer Engineering, University of Michigan—Dearborn, Dearborn, MI 48128, USADepartment of Electrical and Computer Engineering, University of Michigan—Dearborn, Dearborn, MI 48128, USAWith the continuous rise in the energy consumption of buildings, the study and integration of net-zero energy buildings (NZEBs) are essential for mitigating the harmful effects associated with this trend. However, developing an energy management system for such buildings is challenging due to uncertainties surrounding NZEBs. This paper introduces an optimization framework comprising two major stages: (i) renewable energy prediction and (ii) multi-objective optimization. A prediction model is developed to accurately forecast photovoltaic (PV) system output, while a multi-objective optimization model is designed to identify the most efficient ways to produce cooling, heating, and electricity at minimal operational costs. These two stages not only help mitigate uncertainties in NZEBs but also reduce dependence on imported power from the utility grid. Finally, to facilitate the deployment of the proposed framework, a graphical user interface (GUI) has been developed, providing a user-friendly environment for building operators to determine optimal scheduling and oversee the entire system.https://www.mdpi.com/1999-4893/17/11/528energy management systemforecasting modelGUImulti-energy systemnet-zero energy buildingsoptimization |
| spellingShingle | Rayan Khalil Guilherme Vieira Hollweg Akhtar Hussain Wencong Su Van-Hai Bui Assessment of Solar Energy Generation Toward Net-Zero Energy Buildings Algorithms energy management system forecasting model GUI multi-energy system net-zero energy buildings optimization |
| title | Assessment of Solar Energy Generation Toward Net-Zero Energy Buildings |
| title_full | Assessment of Solar Energy Generation Toward Net-Zero Energy Buildings |
| title_fullStr | Assessment of Solar Energy Generation Toward Net-Zero Energy Buildings |
| title_full_unstemmed | Assessment of Solar Energy Generation Toward Net-Zero Energy Buildings |
| title_short | Assessment of Solar Energy Generation Toward Net-Zero Energy Buildings |
| title_sort | assessment of solar energy generation toward net zero energy buildings |
| topic | energy management system forecasting model GUI multi-energy system net-zero energy buildings optimization |
| url | https://www.mdpi.com/1999-4893/17/11/528 |
| work_keys_str_mv | AT rayankhalil assessmentofsolarenergygenerationtowardnetzeroenergybuildings AT guilhermevieirahollweg assessmentofsolarenergygenerationtowardnetzeroenergybuildings AT akhtarhussain assessmentofsolarenergygenerationtowardnetzeroenergybuildings AT wencongsu assessmentofsolarenergygenerationtowardnetzeroenergybuildings AT vanhaibui assessmentofsolarenergygenerationtowardnetzeroenergybuildings |