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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Main Authors: Han B., Zahraoui Y., Mubin M., Mekhilef S., Seyedmahmoudian M., Stojcevski A.
Other Authors: 58128219400
Format: Article
Published: MDPI 2024
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spelling 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
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic degradation cost
home energy management system
optimization algorithm
peak load shifting
thermal comfort
spellingShingle 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
description 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.
author2 58128219400
author_facet 58128219400
Han B.
Zahraoui Y.
Mubin M.
Mekhilef S.
Seyedmahmoudian M.
Stojcevski A.
format Article
author Han B.
Zahraoui Y.
Mubin M.
Mekhilef S.
Seyedmahmoudian M.
Stojcevski A.
author_sort 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
title_full_unstemmed Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model
title_sort optimal strategy for comfort-based home energy management system considering impact of battery degradation cost model
publisher MDPI
publishDate 2024
_version_ 1814061117095280640
score 13.209306