Water-energy nexus: Condition monitoring and the performance optimization of a hybrid cooling system

The steel industry is one of the highest water-intensive sectors. To reduce water consumption in the cooling process of this sector, hybrid cooling systems are proposed. As these systems consume water and energy simultaneously, their operation management needs to be done dynamically, considering wat...

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Autores principales:	Ali Gharavi Hamedani, Masoumeh Bararzadeh Ledari, Yadollah Saboohi
Formato:	article
Lenguaje:	EN
Publicado:	KeAi Communications Co., Ltd. 2021
Materias:	Hybrid water-energy systems Hybrid white-black-box modeling Correlation analysis Operation optimization Water and energy nexus River, lake, and water-supply engineering (General) TC401-506 Water supply for domestic and industrial purposes TD201-500 Energy industries. Energy policy. Fuel trade HD9502-9502.5
Acceso en línea:	https://doaj.org/article/442f695369954b45bb313a1a4c383704
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spelling	oai:doaj.org-article:442f695369954b45bb313a1a4c3837042021-11-24T04:32:57ZWater-energy nexus: Condition monitoring and the performance optimization of a hybrid cooling system2588-912510.1016/j.wen.2021.10.002https://doaj.org/article/442f695369954b45bb313a1a4c3837042021-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S258891252100014Xhttps://doaj.org/toc/2588-9125The steel industry is one of the highest water-intensive sectors. To reduce water consumption in the cooling process of this sector, hybrid cooling systems are proposed. As these systems consume water and energy simultaneously, their operation management needs to be done dynamically, considering water-energy nexus. In the present research, considering regional water and energy scarcities, an operation optimization framework is proposed for the operation management of a direct reduction unit cooling system in a Steel Company. As the behavior of hybrid cooling systems varies over time under the influence of mechanical depreciation and change of environmental conditions, its modeling must be done in a dynamic and precise manner to optimize system performance. In the current study, system modeling is performed by using physical laws (white-box modeling) and machine learning techniques (black-box modeling). Machine learning has been used to modify the deviation of the white-box model from the system situation being caused by equipment degradation. Coupling a dynamic black-box model with the white-box model results in increased accuracy of about 53%. Application of the developed dynamic model, in combination with the proposed framework, has shown that water and energy loss rates could be reduced by 83%; and leads to an 85% saving in possible production reduction. This significant improvement is achieved by the hybrid model's precise prediction of outlet water temperature with 0.91 °C root mean square error; Therefore, using the developed model could help in the improvement of the hybrid cooling system's water and energy efficiency. It is also demonstrated that the model might act as a self-learning model which becomes more precise over time.Ali Gharavi HamedaniMasoumeh Bararzadeh LedariYadollah SaboohiKeAi Communications Co., Ltd.articleHybrid water-energy systemsHybrid white-black-box modelingCorrelation analysisOperation optimizationWater and energy nexusRiver, lake, and water-supply engineering (General)TC401-506Water supply for domestic and industrial purposesTD201-500Energy industries. Energy policy. Fuel tradeHD9502-9502.5ENWater-Energy Nexus, Vol 4, Iss , Pp 149-164 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Hybrid water-energy systems Hybrid white-black-box modeling Correlation analysis Operation optimization Water and energy nexus River, lake, and water-supply engineering (General) TC401-506 Water supply for domestic and industrial purposes TD201-500 Energy industries. Energy policy. Fuel trade HD9502-9502.5
spellingShingle	Hybrid water-energy systems Hybrid white-black-box modeling Correlation analysis Operation optimization Water and energy nexus River, lake, and water-supply engineering (General) TC401-506 Water supply for domestic and industrial purposes TD201-500 Energy industries. Energy policy. Fuel trade HD9502-9502.5 Ali Gharavi Hamedani Masoumeh Bararzadeh Ledari Yadollah Saboohi Water-energy nexus: Condition monitoring and the performance optimization of a hybrid cooling system
description	The steel industry is one of the highest water-intensive sectors. To reduce water consumption in the cooling process of this sector, hybrid cooling systems are proposed. As these systems consume water and energy simultaneously, their operation management needs to be done dynamically, considering water-energy nexus. In the present research, considering regional water and energy scarcities, an operation optimization framework is proposed for the operation management of a direct reduction unit cooling system in a Steel Company. As the behavior of hybrid cooling systems varies over time under the influence of mechanical depreciation and change of environmental conditions, its modeling must be done in a dynamic and precise manner to optimize system performance. In the current study, system modeling is performed by using physical laws (white-box modeling) and machine learning techniques (black-box modeling). Machine learning has been used to modify the deviation of the white-box model from the system situation being caused by equipment degradation. Coupling a dynamic black-box model with the white-box model results in increased accuracy of about 53%. Application of the developed dynamic model, in combination with the proposed framework, has shown that water and energy loss rates could be reduced by 83%; and leads to an 85% saving in possible production reduction. This significant improvement is achieved by the hybrid model's precise prediction of outlet water temperature with 0.91 °C root mean square error; Therefore, using the developed model could help in the improvement of the hybrid cooling system's water and energy efficiency. It is also demonstrated that the model might act as a self-learning model which becomes more precise over time.
format	article
author	Ali Gharavi Hamedani Masoumeh Bararzadeh Ledari Yadollah Saboohi
author_facet	Ali Gharavi Hamedani Masoumeh Bararzadeh Ledari Yadollah Saboohi
author_sort	Ali Gharavi Hamedani
title	Water-energy nexus: Condition monitoring and the performance optimization of a hybrid cooling system
title_short	Water-energy nexus: Condition monitoring and the performance optimization of a hybrid cooling system
title_full	Water-energy nexus: Condition monitoring and the performance optimization of a hybrid cooling system
title_fullStr	Water-energy nexus: Condition monitoring and the performance optimization of a hybrid cooling system
title_full_unstemmed	Water-energy nexus: Condition monitoring and the performance optimization of a hybrid cooling system
title_sort	water-energy nexus: condition monitoring and the performance optimization of a hybrid cooling system
publisher	KeAi Communications Co., Ltd.
publishDate	2021
url	https://doaj.org/article/442f695369954b45bb313a1a4c383704
work_keys_str_mv	AT aligharavihamedani waterenergynexusconditionmonitoringandtheperformanceoptimizationofahybridcoolingsystem AT masoumehbararzadehledari waterenergynexusconditionmonitoringandtheperformanceoptimizationofahybridcoolingsystem AT yadollahsaboohi waterenergynexusconditionmonitoringandtheperformanceoptimizationofahybridcoolingsystem
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Water-energy nexus: Condition monitoring and the performance optimization of a hybrid cooling system

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