Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model
With the deployment of renewable energy generation, home energy storage systems (HESSs), and plug-in electric vehicles (PEVs), home energy management systems (HEMSs) are critical for end users to improve the increasingly complicated energy production and consumption in the home. However, few of the...
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my.uniten.dspace-343362024-10-14T11:19:08Z Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model Han B. Zahraoui Y. Mubin M. Mekhilef S. Seyedmahmoudian M. Stojcevski A. 58128219400 57223913703 25930079700 57928298500 55575761400 55884935900 degradation cost home energy management system optimization algorithm peak load shifting thermal comfort With the deployment of renewable energy generation, home energy storage systems (HESSs), and plug-in electric vehicles (PEVs), home energy management systems (HEMSs) are critical for end users to improve the increasingly complicated energy production and consumption in the home. However, few of the previous works study the impact of different models of battery degradation cost in the optimization strategy of a comfort-based HEMS framework. In this paper, a novel scheduling algorithm based on a mixed-integer programming (MIP) model is proposed for the HEMS. Total cost minimization, peak load shifting, and residents� thermal comfort satisfaction are combined and considered in the optimal scheduling algorithm. The impact of battery degradation costs on the charging and discharging strategy of HESS and PEV is also compared and discussed in this case study. This case study shows that the proposed optimal algorithm of HEMS not only flattens the peak load and satisfies the thermal comfort of residents but also has better flexibility and economic advantages, reducing the electricity cost by 30.84% and total cost by 24.16%. The sensitivity analysis of the parameters for the charging and discharging strategy also guarantees the lowest cost and prolongs the service life of the battery. � 2023 by the authors. Final 2024-10-14T03:19:08Z 2024-10-14T03:19:08Z 2023 Article 10.3390/math11061333 2-s2.0-85151389142 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151389142&doi=10.3390%2fmath11061333&partnerID=40&md5=40a8e013760f893f383cf1354f4b6079 https://irepository.uniten.edu.my/handle/123456789/34336 11 6 1333 All Open Access Gold Open Access MDPI Scopus |
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degradation cost home energy management system optimization algorithm peak load shifting thermal comfort Han B. Zahraoui Y. Mubin M. Mekhilef S. Seyedmahmoudian M. Stojcevski A. Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model |
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With the deployment of renewable energy generation, home energy storage systems (HESSs), and plug-in electric vehicles (PEVs), home energy management systems (HEMSs) are critical for end users to improve the increasingly complicated energy production and consumption in the home. However, few of the previous works study the impact of different models of battery degradation cost in the optimization strategy of a comfort-based HEMS framework. In this paper, a novel scheduling algorithm based on a mixed-integer programming (MIP) model is proposed for the HEMS. Total cost minimization, peak load shifting, and residents� thermal comfort satisfaction are combined and considered in the optimal scheduling algorithm. The impact of battery degradation costs on the charging and discharging strategy of HESS and PEV is also compared and discussed in this case study. This case study shows that the proposed optimal algorithm of HEMS not only flattens the peak load and satisfies the thermal comfort of residents but also has better flexibility and economic advantages, reducing the electricity cost by 30.84% and total cost by 24.16%. The sensitivity analysis of the parameters for the charging and discharging strategy also guarantees the lowest cost and prolongs the service life of the battery. � 2023 by the authors. |
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58128219400 |
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58128219400 Han B. Zahraoui Y. Mubin M. Mekhilef S. Seyedmahmoudian M. Stojcevski A. |
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Article |
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Han B. Zahraoui Y. Mubin M. Mekhilef S. Seyedmahmoudian M. Stojcevski A. |
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Han B. |
title |
Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model |
title_short |
Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model |
title_full |
Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model |
title_fullStr |
Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model |
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Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model |
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optimal strategy for comfort-based home energy management system considering impact of battery degradation cost model |
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MDPI |
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2024 |
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