Privacy-Preserving Energy Management of a Shared Energy Storage System for Smart Buildings: A Federated Deep Reinforcement Learning Approach

Privacy-Preserving Energy Management of a Shared Energy Storage System for Smart Buildings: A Federated Deep Reinforcement Learning Approach

This paper proposes a privacy-preserving energy management of a shared energy storage system (SESS) for multiple smart buildings using federated reinforcement learning (FRL). To preserve the privacy of energy scheduling of buildings connected to the SESS, we present a distributed deep reinforcement...

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Bibliographic Details
Main Authors: Sangyoon Lee, Le Xie, Dae-Hyun Choi
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Sensors
Subjects:
building energy management system
shared energy storage system
federated reinforcement learning
deep reinforcement learning
smart buildings
Online Access:https://www.mdpi.com/1424-8220/21/14/4898

Internet

https://www.mdpi.com/1424-8220/21/14/4898

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