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Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization

In energy management system (EMS), the scheduling of air-conditioning (AC) system has been shown to reduce considerable amount of its power consumption with relatively low implementation cost. However, most scheduling methods lack a systematic approach to ensuring optimal power consumption reduction...

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Main Authors: Haniff, Mohamad Fadzli, Selamat, Hazlina, Khamis, Nuraqilla, Alimin, Ahmad Jais
Format: Article
Language:English
Published: Springer 2018
Subjects:
TH7005-7699 Heating and ventilation. Air conditioning
Online Access:http://eprints.uthm.edu.my/5556/1/AJ%202018%20%28877%29%20Optimized%20scheduling%20for%20an%20airconditioning%20system%20based%20on%20indoor%20thermal%20comfort%20using%20the%20multiobjective%20improved%20global%20particle%20swa.pdf
http://eprints.uthm.edu.my/5556/
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spelling my.uthm.eprints.55562022-01-17T01:09:43Z http://eprints.uthm.edu.my/5556/ Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization Haniff, Mohamad Fadzli Selamat, Hazlina Khamis, Nuraqilla Alimin, Ahmad Jais TH7005-7699 Heating and ventilation. Air conditioning In energy management system (EMS), the scheduling of air-conditioning (AC) system has been shown to reduce considerable amount of its power consumption with relatively low implementation cost. However, most scheduling methods lack a systematic approach to ensuring optimal power consumption reduction and comfort experienced by occupants. The main contribution of this paper is a new optimized AC scheduling approach that focuses on indoor thermal comfort using a new multi-objective optimization algorithm, called the improved global particle swarm optimization (IGPSO), which able to find better optimal solutions faster than its original version, the global particle swarm optimization (GPSO) algorithm. IGPSO is used to model the building characteristics and to find optimum indoor temperature values for the room/building. The proposed technique is based on predicted mean vote (PMV) comfort index that is able to reduce AC power consumption while maintaining indoor comfort throughout its operation. The schedule is set in advance by making use of weather forecast and the estimation of building characteristic parameters. This technique can be implemented on existing buildings with existing HVAC systems with minimal modifications to the HVAC infrastructure. Experimental results show that the proposed method is able to provide good PMV while consuming less power compared to the commonly used extended pre-cooling technique. Springer 2018 Article PeerReviewed text en http://eprints.uthm.edu.my/5556/1/AJ%202018%20%28877%29%20Optimized%20scheduling%20for%20an%20airconditioning%20system%20based%20on%20indoor%20thermal%20comfort%20using%20the%20multiobjective%20improved%20global%20particle%20swa.pdf Haniff, Mohamad Fadzli and Selamat, Hazlina and Khamis, Nuraqilla and Alimin, Ahmad Jais (2018) Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization. Energy Efficiency, 12. pp. 1183-1201. ISSN 1570-6478
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic TH7005-7699 Heating and ventilation. Air conditioning
spellingShingle TH7005-7699 Heating and ventilation. Air conditioning
Haniff, Mohamad Fadzli
Selamat, Hazlina
Khamis, Nuraqilla
Alimin, Ahmad Jais
Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization
description In energy management system (EMS), the scheduling of air-conditioning (AC) system has been shown to reduce considerable amount of its power consumption with relatively low implementation cost. However, most scheduling methods lack a systematic approach to ensuring optimal power consumption reduction and comfort experienced by occupants. The main contribution of this paper is a new optimized AC scheduling approach that focuses on indoor thermal comfort using a new multi-objective optimization algorithm, called the improved global particle swarm optimization (IGPSO), which able to find better optimal solutions faster than its original version, the global particle swarm optimization (GPSO) algorithm. IGPSO is used to model the building characteristics and to find optimum indoor temperature values for the room/building. The proposed technique is based on predicted mean vote (PMV) comfort index that is able to reduce AC power consumption while maintaining indoor comfort throughout its operation. The schedule is set in advance by making use of weather forecast and the estimation of building characteristic parameters. This technique can be implemented on existing buildings with existing HVAC systems with minimal modifications to the HVAC infrastructure. Experimental results show that the proposed method is able to provide good PMV while consuming less power compared to the commonly used extended pre-cooling technique.
format Article
author Haniff, Mohamad Fadzli
Selamat, Hazlina
Khamis, Nuraqilla
Alimin, Ahmad Jais
author_facet Haniff, Mohamad Fadzli
Selamat, Hazlina
Khamis, Nuraqilla
Alimin, Ahmad Jais
author_sort Haniff, Mohamad Fadzli
title Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization
title_short Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization
title_full Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization
title_fullStr Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization
title_full_unstemmed Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization
title_sort optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization
publisher Springer
publishDate 2018
url http://eprints.uthm.edu.my/5556/1/AJ%202018%20%28877%29%20Optimized%20scheduling%20for%20an%20airconditioning%20system%20based%20on%20indoor%20thermal%20comfort%20using%20the%20multiobjective%20improved%20global%20particle%20swa.pdf
http://eprints.uthm.edu.my/5556/
_version_ 1738581391134687232
score 13.211869

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