Ensemble modelling of hygrothermal system for multi- objectives model predictive controllers

An air conditioner maintains occupants’ thermal comfort; however, it is also power-hungry in which leads to high electricity consumption. Maintaining thermal comfort while minimising electrical power consumption is difficult, especially when the weather-related inputs are not predictable. This leads...

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Main Author:	Mohd. Hussein, Shamsul Faisal
Format:	Thesis
Language:	English
Published:	2022
Subjects:	TA Engineering (General) Civil engineering (General)
Online Access:	http://eprints.utm.my/id/eprint/100413/1/ShamsulFaisalMohdPMJIIT2022.pdf
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id	my-utm-ep.100413
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spelling	my-utm-ep.1004132023-04-13T03:35:51Z Ensemble modelling of hygrothermal system for multi- objectives model predictive controllers 2022 Mohd. Hussein, Shamsul Faisal TA Engineering (General). Civil engineering (General) An air conditioner maintains occupants’ thermal comfort; however, it is also power-hungry in which leads to high electricity consumption. Maintaining thermal comfort while minimising electrical power consumption is difficult, especially when the weather-related inputs are not predictable. This leads to overcooling due to undershoot and undercooling due to overshoot. Undercooling causes discomfort, while overcooling causes discomfort and high-power usage. To minimise this problem, the implementation of model-based predictive controllers can be developed to produce necessary pre-emptive control decisions based on the output of the embedded simulation model in the controller. However, the simulation model must be accurate for the best result. This project develops accuracy-improved mathematical models that represent the dynamic hygrothermal behaviour of a laboratory in aiding future potential energy-efficient predictive controllers. This is to maintain the thermal comfort level in the laboratory while minimising power consumption. Two thermal comfort variables were modelled to maintain two different desired setpoints simultaneously in the future. First, the empirical modelling was developed to capture the dynamics of the temperature and humidity behaviours of the laboratory using three existing standard methods, which were: (1) autoregressive–moving-average (ARMA) model; (2) transfer function (TF) model; and (3) nonlinear autoregressive exogenous model (NARX) model. Second, the ensemble methods were implemented to increase the simulation accuracy of the developed modelling by summing up the output values from all three developed models – prior to summation, the output of each of the models was multiplied by the weight value assigned for each of the models. The values of these weights were determined using the following three ensemble methods: (1) weighted average; (2) least square technique (LST) / least square method (LSM); and (3) genetic algorithm (GA). All models’ simulation outputs were compared with the actual data for accuracy benchmarking. Results showed that the most accurate ensemble models have better accuracies than the most accurate individual models developed in this research while being simulated with the testing data set in each simulation case. The improvements in the air temperature simulation models are by 3.40%, 7.38%, and 8.69% each for one-, five-, and ten-minute(s) simulation ahead, while the improvements in the relative humidity simulation models are by 0.96%, 1.35%, and 2.38% each for one-, five-, and ten-minute(s) simulation ahead. The accuracy-improved models can then be utilised in model-based predictive controllers for maintaining occupants’ thermal comfort in a building while minimising the air conditioners’ power consumption for energy saving and environmental conservation. 2022 Thesis http://eprints.utm.my/id/eprint/100413/ http://eprints.utm.my/id/eprint/100413/1/ShamsulFaisalMohdPMJIIT2022.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:150807 phd doctoral Universiti Teknologi Malaysia, Malaysia-Japan International Institute of Technology Malaysia-Japan International Institute of Technology
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TA Engineering (General) Civil engineering (General)
spellingShingle	TA Engineering (General) Civil engineering (General) Mohd. Hussein, Shamsul Faisal Ensemble modelling of hygrothermal system for multi- objectives model predictive controllers
description	An air conditioner maintains occupants’ thermal comfort; however, it is also power-hungry in which leads to high electricity consumption. Maintaining thermal comfort while minimising electrical power consumption is difficult, especially when the weather-related inputs are not predictable. This leads to overcooling due to undershoot and undercooling due to overshoot. Undercooling causes discomfort, while overcooling causes discomfort and high-power usage. To minimise this problem, the implementation of model-based predictive controllers can be developed to produce necessary pre-emptive control decisions based on the output of the embedded simulation model in the controller. However, the simulation model must be accurate for the best result. This project develops accuracy-improved mathematical models that represent the dynamic hygrothermal behaviour of a laboratory in aiding future potential energy-efficient predictive controllers. This is to maintain the thermal comfort level in the laboratory while minimising power consumption. Two thermal comfort variables were modelled to maintain two different desired setpoints simultaneously in the future. First, the empirical modelling was developed to capture the dynamics of the temperature and humidity behaviours of the laboratory using three existing standard methods, which were: (1) autoregressive–moving-average (ARMA) model; (2) transfer function (TF) model; and (3) nonlinear autoregressive exogenous model (NARX) model. Second, the ensemble methods were implemented to increase the simulation accuracy of the developed modelling by summing up the output values from all three developed models – prior to summation, the output of each of the models was multiplied by the weight value assigned for each of the models. The values of these weights were determined using the following three ensemble methods: (1) weighted average; (2) least square technique (LST) / least square method (LSM); and (3) genetic algorithm (GA). All models’ simulation outputs were compared with the actual data for accuracy benchmarking. Results showed that the most accurate ensemble models have better accuracies than the most accurate individual models developed in this research while being simulated with the testing data set in each simulation case. The improvements in the air temperature simulation models are by 3.40%, 7.38%, and 8.69% each for one-, five-, and ten-minute(s) simulation ahead, while the improvements in the relative humidity simulation models are by 0.96%, 1.35%, and 2.38% each for one-, five-, and ten-minute(s) simulation ahead. The accuracy-improved models can then be utilised in model-based predictive controllers for maintaining occupants’ thermal comfort in a building while minimising the air conditioners’ power consumption for energy saving and environmental conservation.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Mohd. Hussein, Shamsul Faisal
author_facet	Mohd. Hussein, Shamsul Faisal
author_sort	Mohd. Hussein, Shamsul Faisal
title	Ensemble modelling of hygrothermal system for multi- objectives model predictive controllers
title_short	Ensemble modelling of hygrothermal system for multi- objectives model predictive controllers
title_full	Ensemble modelling of hygrothermal system for multi- objectives model predictive controllers
title_fullStr	Ensemble modelling of hygrothermal system for multi- objectives model predictive controllers
title_full_unstemmed	Ensemble modelling of hygrothermal system for multi- objectives model predictive controllers
title_sort	ensemble modelling of hygrothermal system for multi- objectives model predictive controllers
granting_institution	Universiti Teknologi Malaysia, Malaysia-Japan International Institute of Technology
granting_department	Malaysia-Japan International Institute of Technology
publishDate	2022
url	http://eprints.utm.my/id/eprint/100413/1/ShamsulFaisalMohdPMJIIT2022.pdf
_version_	1776100689660870656

Ensemble modelling of hygrothermal system for multi- objectives model predictive controllers

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