A grid-connected optimal hybrid PV-BES System sizing for Malaysian Commercial Buildings

In this article, the optimal sizing of hybrid solar photovoltaic and battery energy storage systems is evaluated with respect to rooftop space and feed-in tariff rates. The battery scheduling is performed using a proposed rule-based energy management strategy. The rules are formulated based on the d...

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Main Authors: Hossain, Jahangir, Saeed, Nagham, Abdul Kadir, Aida Fazliana, Shareef, Hussain, Manojkumar, Rampelli, Hanafi, Ainain Nur
Format: Article
Language:English
Published: MDPI AG 2023
Online Access:http://eprints.utem.edu.my/id/eprint/27494/2/0033429072023269.PDF
http://eprints.utem.edu.my/id/eprint/27494/
https://www.mdpi.com/2071-1050/15/13/10564
https://doi.org/10.3390/su151310564
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spelling my.utem.eprints.274942024-07-04T12:00:59Z http://eprints.utem.edu.my/id/eprint/27494/ A grid-connected optimal hybrid PV-BES System sizing for Malaysian Commercial Buildings Hossain, Jahangir Saeed, Nagham Abdul Kadir, Aida Fazliana Shareef, Hussain Manojkumar, Rampelli Hanafi, Ainain Nur In this article, the optimal sizing of hybrid solar photovoltaic and battery energy storage systems is evaluated with respect to rooftop space and feed-in tariff rates. The battery scheduling is performed using a proposed rule-based energy management strategy. The rules are formulated based on the demand limit, PV export power limit, and state of charge of the battery. Furthermore, optimization modeling with initial choices of parameters and constraints in terms of solar photovoltaic and battery energy storage capabilities is developed to minimize the total net present cost. The hourly values of solar irradiance, air temperature, electrical loads, and electricity rates are considered the inputs of the optimization process. The optimization results are achieved using particle swarm optimization and validated through an uncertainty analysis. It is observed that an optimal photovoltaic and battery energy storage system can reduce the cost of electricity by 12.33%, including the sale of 5944.029 kWh of electricity to the grid. Furthermore, energy consumption, peak demand, and greenhouse gas emissions are reduced by 13.71%, 5.85%, and 62.59%, respectively. A comprehensive analysis between the variable and fixed data for the load, energy from PV, batteries, and the grid, and costs demonstrates that the optimal sizing of photovoltaic and battery energy storage systems with the best mix of energy from PV, batteries, and the grid provides the optimal solution for the proposed configuration. MDPI AG 2023-07 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/27494/2/0033429072023269.PDF Hossain, Jahangir and Saeed, Nagham and Abdul Kadir, Aida Fazliana and Shareef, Hussain and Manojkumar, Rampelli and Hanafi, Ainain Nur (2023) A grid-connected optimal hybrid PV-BES System sizing for Malaysian Commercial Buildings. Sustainability (Switzerland), 15 (13). pp. 1-20. ISSN 2071-1050 https://www.mdpi.com/2071-1050/15/13/10564 https://doi.org/10.3390/su151310564
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description In this article, the optimal sizing of hybrid solar photovoltaic and battery energy storage systems is evaluated with respect to rooftop space and feed-in tariff rates. The battery scheduling is performed using a proposed rule-based energy management strategy. The rules are formulated based on the demand limit, PV export power limit, and state of charge of the battery. Furthermore, optimization modeling with initial choices of parameters and constraints in terms of solar photovoltaic and battery energy storage capabilities is developed to minimize the total net present cost. The hourly values of solar irradiance, air temperature, electrical loads, and electricity rates are considered the inputs of the optimization process. The optimization results are achieved using particle swarm optimization and validated through an uncertainty analysis. It is observed that an optimal photovoltaic and battery energy storage system can reduce the cost of electricity by 12.33%, including the sale of 5944.029 kWh of electricity to the grid. Furthermore, energy consumption, peak demand, and greenhouse gas emissions are reduced by 13.71%, 5.85%, and 62.59%, respectively. A comprehensive analysis between the variable and fixed data for the load, energy from PV, batteries, and the grid, and costs demonstrates that the optimal sizing of photovoltaic and battery energy storage systems with the best mix of energy from PV, batteries, and the grid provides the optimal solution for the proposed configuration.
format Article
author Hossain, Jahangir
Saeed, Nagham
Abdul Kadir, Aida Fazliana
Shareef, Hussain
Manojkumar, Rampelli
Hanafi, Ainain Nur
spellingShingle Hossain, Jahangir
Saeed, Nagham
Abdul Kadir, Aida Fazliana
Shareef, Hussain
Manojkumar, Rampelli
Hanafi, Ainain Nur
A grid-connected optimal hybrid PV-BES System sizing for Malaysian Commercial Buildings
author_facet Hossain, Jahangir
Saeed, Nagham
Abdul Kadir, Aida Fazliana
Shareef, Hussain
Manojkumar, Rampelli
Hanafi, Ainain Nur
author_sort Hossain, Jahangir
title A grid-connected optimal hybrid PV-BES System sizing for Malaysian Commercial Buildings
title_short A grid-connected optimal hybrid PV-BES System sizing for Malaysian Commercial Buildings
title_full A grid-connected optimal hybrid PV-BES System sizing for Malaysian Commercial Buildings
title_fullStr A grid-connected optimal hybrid PV-BES System sizing for Malaysian Commercial Buildings
title_full_unstemmed A grid-connected optimal hybrid PV-BES System sizing for Malaysian Commercial Buildings
title_sort grid-connected optimal hybrid pv-bes system sizing for malaysian commercial buildings
publisher MDPI AG
publishDate 2023
url http://eprints.utem.edu.my/id/eprint/27494/2/0033429072023269.PDF
http://eprints.utem.edu.my/id/eprint/27494/
https://www.mdpi.com/2071-1050/15/13/10564
https://doi.org/10.3390/su151310564
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