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2023 | OriginalPaper | Chapter

5. Application of Machine Learning and Artificial Intelligence in Design, Optimization, and Control of VRF Systems

Authors : Ali Sohani, Fatemeh Delfani, Mohammadmehdi Hosseini, Yabin Guo, Ala Sadooghi, Siamak Hoseinzadeh, Hoseyn Sayyaadi

Published in: Variable Refrigerant Flow Systems

Publisher: Springer Nature Singapore

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Abstract

Variable refrigerant flow (VRF) technologies, also known as variable volume refrigerant (VRV) systems, are taken into account as one of the most efficient, environmentally friendly, and economically viable alternatives for providing cooling and heating demands in the buildings. The increasing tendency towards using VRF technologies, in addition to the huge progress in the computer science, have led to using machine learning and artificial intelligence for design, optimization, and control of such systems with a fast upward trend. Taking these points into account, this chapter aims at giving an overview of artificial intelligence technologies and machine learning methods utilization for VRF systems. It is done by describing their application in design, optimization, and control of them.

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previous chapter Analysis of Air Side Cooling and Dehumidification Performance in Evaporator in Direct Expansion (DX) Variable Refrigerant Flow (VRF) Air-Conditioning (A/C) System

next chapter Energy Efficient Variable Refrigerant Flow Systems for Modern Buildings

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Title: Application of Machine Learning and Artificial Intelligence in Design, Optimization, and Control of VRF Systems
Authors: Ali Sohani
Fatemeh Delfani
Mohammadmehdi Hosseini
Yabin Guo
Ala Sadooghi
Siamak Hoseinzadeh
Hoseyn Sayyaadi
Publisher: Springer Nature Singapore
Book: Variable Refrigerant Flow Systems
Print ISBN: 978-981-19-6832-7

Electronic ISBN: 978-981-19-6833-4

Copyright Year: 2023
DOI: https://doi.org/10.1007/978-981-19-6833-4_5

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