A multi-objective optimization of a building’s total heating and cooling loads and total costs in various climatic situations using response surface methodology

Excessive rise in energy consumption has been one of the major predicaments of recent decades. Among all the sectors, residential buildings are one of the main consumers of energy resources. Because air conditioning systems are the main ground for using energy inside houses, researchers have propose...

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Autores principales:	Mohammadreza Baghoolizadeh, Reza Rostamzadeh-Renani, Mohammad Rostamzadeh-Renani, Davood Toghraie
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Cooling set point temperature Insulator Heating set point temperature Multi-objective-optimization Response surface methodology Total heating and cooling loads Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/ab0e92c25b114446a729516f354c3469
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spelling	oai:doaj.org-article:ab0e92c25b114446a729516f354c34692021-11-18T04:50:08ZA multi-objective optimization of a building’s total heating and cooling loads and total costs in various climatic situations using response surface methodology2352-484710.1016/j.egyr.2021.10.092https://doaj.org/article/ab0e92c25b114446a729516f354c34692021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2352484721011100https://doaj.org/toc/2352-4847Excessive rise in energy consumption has been one of the major predicaments of recent decades. Among all the sectors, residential buildings are one of the main consumers of energy resources. Because air conditioning systems are the main ground for using energy inside houses, researchers have proposed diverse methods of reducing energy loss such as encapsulating insulators in wall structures. In this paper, the main focus is to calculate and then optimize the total heating and cooling loads as well as the total costs. The building model was simulated in cities with different climatic situations using EnergyPlus software. For optimization, five design variables were determined and 300 Design of Experiment points were considered for each city to measure the Objective Functions, which are the building’s total load and cost. To find the optimal states, Response Surface Methodology (RSM) is utilized to predict continuous functions from discrete data of experiments. Consequently, total load and total costs of building in various climatic conditions were improved by a range of 2%–16%, and the Static Payback Period and Human Heating Comfort were ameliorated dramatically.Mohammadreza BaghoolizadehReza Rostamzadeh-RenaniMohammad Rostamzadeh-RenaniDavood ToghraieElsevierarticleCooling set point temperatureInsulatorHeating set point temperatureMulti-objective-optimizationResponse surface methodologyTotal heating and cooling loadsElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENEnergy Reports, Vol 7, Iss , Pp 7520-7538 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Cooling set point temperature Insulator Heating set point temperature Multi-objective-optimization Response surface methodology Total heating and cooling loads Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Cooling set point temperature Insulator Heating set point temperature Multi-objective-optimization Response surface methodology Total heating and cooling loads Electrical engineering. Electronics. Nuclear engineering TK1-9971 Mohammadreza Baghoolizadeh Reza Rostamzadeh-Renani Mohammad Rostamzadeh-Renani Davood Toghraie A multi-objective optimization of a building’s total heating and cooling loads and total costs in various climatic situations using response surface methodology
description	Excessive rise in energy consumption has been one of the major predicaments of recent decades. Among all the sectors, residential buildings are one of the main consumers of energy resources. Because air conditioning systems are the main ground for using energy inside houses, researchers have proposed diverse methods of reducing energy loss such as encapsulating insulators in wall structures. In this paper, the main focus is to calculate and then optimize the total heating and cooling loads as well as the total costs. The building model was simulated in cities with different climatic situations using EnergyPlus software. For optimization, five design variables were determined and 300 Design of Experiment points were considered for each city to measure the Objective Functions, which are the building’s total load and cost. To find the optimal states, Response Surface Methodology (RSM) is utilized to predict continuous functions from discrete data of experiments. Consequently, total load and total costs of building in various climatic conditions were improved by a range of 2%–16%, and the Static Payback Period and Human Heating Comfort were ameliorated dramatically.
format	article
author	Mohammadreza Baghoolizadeh Reza Rostamzadeh-Renani Mohammad Rostamzadeh-Renani Davood Toghraie
author_facet	Mohammadreza Baghoolizadeh Reza Rostamzadeh-Renani Mohammad Rostamzadeh-Renani Davood Toghraie
author_sort	Mohammadreza Baghoolizadeh
title	A multi-objective optimization of a building’s total heating and cooling loads and total costs in various climatic situations using response surface methodology
title_short	A multi-objective optimization of a building’s total heating and cooling loads and total costs in various climatic situations using response surface methodology
title_full	A multi-objective optimization of a building’s total heating and cooling loads and total costs in various climatic situations using response surface methodology
title_fullStr	A multi-objective optimization of a building’s total heating and cooling loads and total costs in various climatic situations using response surface methodology
title_full_unstemmed	A multi-objective optimization of a building’s total heating and cooling loads and total costs in various climatic situations using response surface methodology
title_sort	multi-objective optimization of a building’s total heating and cooling loads and total costs in various climatic situations using response surface methodology
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/ab0e92c25b114446a729516f354c3469
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A multi-objective optimization of a building’s total heating and cooling loads and total costs in various climatic situations using response surface methodology

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