A high-resolution daily experimental performance evaluation of a large-scale industrial vapor-compression refrigeration system based on real-time IoT data monitoring technology. (October 2021)
- Record Type:
- Journal Article
- Title:
- A high-resolution daily experimental performance evaluation of a large-scale industrial vapor-compression refrigeration system based on real-time IoT data monitoring technology. (October 2021)
- Main Title:
- A high-resolution daily experimental performance evaluation of a large-scale industrial vapor-compression refrigeration system based on real-time IoT data monitoring technology
- Authors:
- Momeni, Mahdi
Jani, S.
Sohani, Ali
Jani, Saber
Rahpeyma, Elaheh - Abstract:
- Highlights: An industrial refrigeration system in large scale was comprehensively investigated. A high-resolution sensor monitoring technology based on Internet of Things is used. Dynamic analysis was done from energy, exergy, and exergoeconomic perspectives. 67% and 70% of cooling demand and power consumption is seen during peak hours. Total cost rate varies from 0.89 $/h during midnight to 1.10 $/h for noon. Abstract: This paper studies a novel comprehensive experimental dynamic performance analysis of a large-scale industrial vapor-compression refrigeration system as a part of a discrete cooling system with the aim of system daily parameter investigation. An innovative high-resolution real-time data monitoring is implemented on the system based on precise internet-of-things sensor technology. For precise evaluation of system performance, energy, exergy, and exergoeconomic aspects were considered to achieve daily results for future energy planning. The results demonstrates that high parameter variations occur during peak hours, while around 70% of both the total refrigeration cooling demand and the total power consumption was during the peak period. Moreover, the system's total exergy destruction rate raised by 88.4% at the peak hours, while the exergy efficiency attained between 27 and 35% throughout the day. In addition, the price of the evaporator outlet air, the desired product of the system, decreased from 96.9 $/GJ at midnight to 61.1 $/GJ at noon peak hours. In thisHighlights: An industrial refrigeration system in large scale was comprehensively investigated. A high-resolution sensor monitoring technology based on Internet of Things is used. Dynamic analysis was done from energy, exergy, and exergoeconomic perspectives. 67% and 70% of cooling demand and power consumption is seen during peak hours. Total cost rate varies from 0.89 $/h during midnight to 1.10 $/h for noon. Abstract: This paper studies a novel comprehensive experimental dynamic performance analysis of a large-scale industrial vapor-compression refrigeration system as a part of a discrete cooling system with the aim of system daily parameter investigation. An innovative high-resolution real-time data monitoring is implemented on the system based on precise internet-of-things sensor technology. For precise evaluation of system performance, energy, exergy, and exergoeconomic aspects were considered to achieve daily results for future energy planning. The results demonstrates that high parameter variations occur during peak hours, while around 70% of both the total refrigeration cooling demand and the total power consumption was during the peak period. Moreover, the system's total exergy destruction rate raised by 88.4% at the peak hours, while the exergy efficiency attained between 27 and 35% throughout the day. In addition, the price of the evaporator outlet air, the desired product of the system, decreased from 96.9 $/GJ at midnight to 61.1 $/GJ at noon peak hours. In this period, the total cost rate for the system increased from 0.89 $/h to 1.10 $/h. The data obtained is not only beneficial regarding dynamic performance analysis of the refrigeration cycle but also can assist for executive purposes regarding energy management and further profit makings. … (more)
- Is Part Of:
- Sustainable energy technologies and assessments. Volume 47(2021)
- Journal:
- Sustainable energy technologies and assessments
- Issue:
- Volume 47(2021)
- Issue Display:
- Volume 47, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 47
- Issue:
- 2021
- Issue Sort Value:
- 2021-0047-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-10
- Subjects:
- Dynamic thermodynamic analysis -- Real-time exergoeconomic analysis -- Vapor-compression refrigeration cycle -- Internet-of-things (IoT) -- Sensor technology
Renewable energy sources -- Periodicals
Energy development -- Technological innovations -- Periodicals
Electric power production -- Periodicals
Energy storage -- Periodicals
333.79 - Journal URLs:
- http://www.sciencedirect.com/science/journal/22131388/ ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.seta.2021.101427 ↗
- Languages:
- English
- ISSNs:
- 2213-1388
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 19700.xml