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IoT/AI Control of VRF Distributed Building Air-Conditioners / by Chuzo Ninagawa.

Springer eBooks EBA - Engineering Collection 2024 Available online

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Format:
Book
Author/Creator:
Ninagawa, Chuzo, author.
Language:
English
Subjects (All):
Buildings--Environmental engineering.
Buildings.
Automation.
Internet of things.
Machine learning.
Building Physics, HVAC.
Internet of Things.
Machine Learning.
Local Subjects:
Building Physics, HVAC.
Automation.
Internet of Things.
Machine Learning.
Physical Description:
1 online resource (214 pages)
Edition:
1st ed. 2024.
Place of Publication:
Singapore : Springer Nature Singapore : Imprint: Springer, 2024.
Summary:
This book describes new energy service controls of VRF (Variable Refrigerant Flow) air-conditioners, i.e., distributed-type air-conditioners for commercial buildings in the near future, in the context of the energy savings for CO2 reduction and the reform of the electric power system. In other words, this book introduces the state-of-the-art technology of the next-generation distributed building air-conditioning energy service system, from IoT cloud control to AI optimal control, as well as standards for the smart grid supply and demand adjustment market. Rather than simple saving energy by On Off operations or shifting set- temperatures, the author proposes technology that sends numerical commands for the air-conditioner inverters directly from the cloud. By using this innovative IoT method, this book describes how to realizes the AI optimal cloud control as a cluster of air-conditioners while machine-learning of each air conditioner's situation.
Contents:
Chapter 1. Innovations in Air-conditioning Energy Control
Chapter 2. BACnet Communication Control
Chapter 3. LON Communication Control
Chapter 4. WEB Cloud Communication Control
Chapter 5. Virtual Wattmeter for VRF Air-conditioner
Chapter 6. Fast Automated Demand Response
Chapter 7. Deep Learning for FastADR
Chapter 8. IEEJ Power Supply-Demand Adjustment Service
Chapter 9. OpenADR Communication Control
Chapter 10. Optimal Real-Time Pricing Control
Chapter 11. Power Control by Reinforcement Learning.
Notes:
Includes bibliographical references.
Other Format:
Print version: Ninagawa, Chuzo IoT/AI Control of VRF Distributed Building Air-Conditioners
ISBN:
9789819991990

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