Building Energy Management through a Distributed Fuzzy Inference System

Buildings consume significant world�s energy resources, approximately 32% of the total primary energy. The rapid depletion of energy resources, has imparted researchers to focus on energy conservation and wastage. The next generation of smart buildings is becoming a trend to cope with the needs of e...

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Main Authors: Mohd Nor, Nursyarizal, Elamvazuthi, I, Perumal, Nallagownden
Format: Citation Index Journal
Published: 2013
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Online Access:http://eprints.utp.edu.my/11161/2/IJET%20Pervez.docx
http://eprints.utp.edu.my/11161/
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Institution: Universiti Teknologi Petronas
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spelling my.utp.eprints.111612014-02-16T23:41:44Z Building Energy Management through a Distributed Fuzzy Inference System Mohd Nor, Nursyarizal Elamvazuthi, I Perumal, Nallagownden TK Electrical engineering. Electronics Nuclear engineering Buildings consume significant world�s energy resources, approximately 32% of the total primary energy. The rapid depletion of energy resources, has imparted researchers to focus on energy conservation and wastage. The next generation of smart buildings is becoming a trend to cope with the needs of energy and environmental ease in buildings. This advances the intelligent control of building to fulfill the occupants� need. Intelligent system control for sustainable buildings is dynamic and highly complex. Building information accuracy with an effective controller scheme is a challenging task. This paper presents the fuzzy control system architecture (FCSA) for resolving the conflict of maintaining the inhabitants comfort index and the energy consumption in buildings. It also infers the graphical relationship between energy consumption and comfort parameters. With a distributed fuzzy inference system (FIS), control has been developed for temperature, air quality and artificial lighting comfort parameters. Model simulation has been carried out and control factors have been discussed. The FIS models have also been validated with implication of change function. The presented control system is capable of achieving energy conservation in the buildings. 2013-08 Citation Index Journal PeerReviewed application/msword http://eprints.utp.edu.my/11161/2/IJET%20Pervez.docx Mohd Nor, Nursyarizal and Elamvazuthi, I and Perumal, Nallagownden (2013) Building Energy Management through a Distributed Fuzzy Inference System. [Citation Index Journal] http://eprints.utp.edu.my/11161/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Mohd Nor, Nursyarizal
Elamvazuthi, I
Perumal, Nallagownden
Building Energy Management through a Distributed Fuzzy Inference System
description Buildings consume significant world�s energy resources, approximately 32% of the total primary energy. The rapid depletion of energy resources, has imparted researchers to focus on energy conservation and wastage. The next generation of smart buildings is becoming a trend to cope with the needs of energy and environmental ease in buildings. This advances the intelligent control of building to fulfill the occupants� need. Intelligent system control for sustainable buildings is dynamic and highly complex. Building information accuracy with an effective controller scheme is a challenging task. This paper presents the fuzzy control system architecture (FCSA) for resolving the conflict of maintaining the inhabitants comfort index and the energy consumption in buildings. It also infers the graphical relationship between energy consumption and comfort parameters. With a distributed fuzzy inference system (FIS), control has been developed for temperature, air quality and artificial lighting comfort parameters. Model simulation has been carried out and control factors have been discussed. The FIS models have also been validated with implication of change function. The presented control system is capable of achieving energy conservation in the buildings.
format Citation Index Journal
author Mohd Nor, Nursyarizal
Elamvazuthi, I
Perumal, Nallagownden
author_facet Mohd Nor, Nursyarizal
Elamvazuthi, I
Perumal, Nallagownden
author_sort Mohd Nor, Nursyarizal
title Building Energy Management through a Distributed Fuzzy Inference System
title_short Building Energy Management through a Distributed Fuzzy Inference System
title_full Building Energy Management through a Distributed Fuzzy Inference System
title_fullStr Building Energy Management through a Distributed Fuzzy Inference System
title_full_unstemmed Building Energy Management through a Distributed Fuzzy Inference System
title_sort building energy management through a distributed fuzzy inference system
publishDate 2013
url http://eprints.utp.edu.my/11161/2/IJET%20Pervez.docx
http://eprints.utp.edu.my/11161/
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