Machine Learning Approach to Predict the Performance of a Stratified Thermal Energy Storage Tank at a District Cooling Plant Using Sensor Data

Machine Learning Approach to Predict the Performance of a Stratified Thermal Energy Storage Tank at a District Cooling Plant Using Sensor Data

In the energy management of district cooling plants, the thermal energy storage tank is critical. As a result, it is essential to keep track of TES results. The performance of the TES has been measured using a variety of methodologies, both numerical and analytical. In this study, the performance of...

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Bibliographic Details
Main Authors: Afzal Ahmed Soomro, Ainul Akmar Mokhtar, Waleligne Molla Salilew, Zainal Ambri Abdul Karim, Aijaz Abbasi, Najeebullah Lashari, Syed Muslim Jameel
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Sensors
Subjects:
temperature distribution
thermal energy storage
thermocline thickness
artificial neural networks
support vector machine
k-nearest neighbor district colling
Online Access:https://www.mdpi.com/1424-8220/22/19/7687

Internet

https://www.mdpi.com/1424-8220/22/19/7687

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