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6. Demand Side Equipment Control in Virtual Power Plant

  • 2022
  • OriginalPaper
  • Chapter
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Author
Chuzo Ninagawa
Published in
Virtual Power Plant System Integration Technology
Publisher
Springer Singapore

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Abstract

The chapter delves into the use of FastADR response prediction for building multi-type air-conditioning systems, highlighting the importance of accurate power suppression commands. It introduces neural networks and deep learning techniques to predict air-conditioning power consumption and room temperature variations, aiming to optimize comfort and efficiency. The text also discusses methods to compensate for tracking errors using storage batteries, ensuring better adherence to demand response commands. Additionally, it presents innovative approaches like the FastADR packetized rotation method to distribute power suppression commands effectively, minimizing the impact on occupant comfort.
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previous chapter Battery Control in Virtual Power Plant
next chapter Virtual Power Plant Performance
Title
Demand Side Equipment Control in Virtual Power Plant
Author
Chuzo Ninagawa
Copyright Year
2022
Publisher
Springer Singapore
Book
Virtual Power Plant System Integration Technology

Print ISBN: 978-981-16-6147-1

Electronic ISBN: 978-981-16-6148-8

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-981-16-6148-8_6
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