Green Building Energy Cost Optimization With Deep Belief Network and Firefly Algorithm

In this research, we propose a multi-objective optimization framework to minimize the energy cost while maintain the indoor air quality. The proposed framework is consisted with two stages: predictive modeling stage and multi-objective optimization stage. In the first stage, artificial neural networ...

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Autores principales:	Yan Liao, Yong Liu, Chaoyu Chen, Lili Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	green building HVAC feature selection deep learning multi-objective optimization General Works A
Acceso en línea:	https://doaj.org/article/3f0fe59a31574dfd951b9a55b78287cf
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id	oai:doaj.org-article:3f0fe59a31574dfd951b9a55b78287cf
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spelling	oai:doaj.org-article:3f0fe59a31574dfd951b9a55b78287cf2021-12-01T21:40:46ZGreen Building Energy Cost Optimization With Deep Belief Network and Firefly Algorithm2296-598X10.3389/fenrg.2021.805206https://doaj.org/article/3f0fe59a31574dfd951b9a55b78287cf2021-12-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fenrg.2021.805206/fullhttps://doaj.org/toc/2296-598XIn this research, we propose a multi-objective optimization framework to minimize the energy cost while maintain the indoor air quality. The proposed framework is consisted with two stages: predictive modeling stage and multi-objective optimization stage. In the first stage, artificial neural networks are applied to predict the energy utility in real-time. In the second stage, an optimization algorithm namely firefly algorithm is utilized to reduce the energy cost while maintaining the required IAQ conditions. Industrial data collected from a commercial building in central business district in Chengdu, China is utilized in this study. The results produced by the optimization framework show that this strategy reduces energy cost by optimizing operations within the HAVC system.Yan LiaoYong LiuChaoyu ChenLili ZhangFrontiers Media S.A.articlegreen buildingHVACfeature selectiondeep learningmulti-objective optimizationGeneral WorksAENFrontiers in Energy Research, Vol 9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	green building HVAC feature selection deep learning multi-objective optimization General Works A
spellingShingle	green building HVAC feature selection deep learning multi-objective optimization General Works A Yan Liao Yong Liu Chaoyu Chen Lili Zhang Green Building Energy Cost Optimization With Deep Belief Network and Firefly Algorithm
description	In this research, we propose a multi-objective optimization framework to minimize the energy cost while maintain the indoor air quality. The proposed framework is consisted with two stages: predictive modeling stage and multi-objective optimization stage. In the first stage, artificial neural networks are applied to predict the energy utility in real-time. In the second stage, an optimization algorithm namely firefly algorithm is utilized to reduce the energy cost while maintaining the required IAQ conditions. Industrial data collected from a commercial building in central business district in Chengdu, China is utilized in this study. The results produced by the optimization framework show that this strategy reduces energy cost by optimizing operations within the HAVC system.
format	article
author	Yan Liao Yong Liu Chaoyu Chen Lili Zhang
author_facet	Yan Liao Yong Liu Chaoyu Chen Lili Zhang
author_sort	Yan Liao
title	Green Building Energy Cost Optimization With Deep Belief Network and Firefly Algorithm
title_short	Green Building Energy Cost Optimization With Deep Belief Network and Firefly Algorithm
title_full	Green Building Energy Cost Optimization With Deep Belief Network and Firefly Algorithm
title_fullStr	Green Building Energy Cost Optimization With Deep Belief Network and Firefly Algorithm
title_full_unstemmed	Green Building Energy Cost Optimization With Deep Belief Network and Firefly Algorithm
title_sort	green building energy cost optimization with deep belief network and firefly algorithm
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/3f0fe59a31574dfd951b9a55b78287cf
work_keys_str_mv	AT yanliao greenbuildingenergycostoptimizationwithdeepbeliefnetworkandfireflyalgorithm AT yongliu greenbuildingenergycostoptimizationwithdeepbeliefnetworkandfireflyalgorithm AT chaoyuchen greenbuildingenergycostoptimizationwithdeepbeliefnetworkandfireflyalgorithm AT lilizhang greenbuildingenergycostoptimizationwithdeepbeliefnetworkandfireflyalgorithm
_version_	1718404270867349504

Green Building Energy Cost Optimization With Deep Belief Network and Firefly Algorithm

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