A Fast and Optimal Smart Home Energy Management System: State-Space Approximate Dynamic Programming

A Fast and Optimal Smart Home Energy Management System: State-Space Approximate Dynamic Programming

Dynamic programming (DP) can be used to generate the optimal schedules of a smart home energy management system (SHEMS), however, it is computationally difficult because we have to loop over all the possible states, decisions and outcomes. This paper proposes a novel state-space approximate dynamic...

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Bibliographic Details
Main Authors: Zhiheng Zhao, Chanaka Keerthisinghe
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
PV-storage systems
smart home energy management
state-space approximate dynamic programming
machine learning
long short-term memory recurrent neural networks
Online Access:https://ieeexplore.ieee.org/document/9195464/

Internet

https://ieeexplore.ieee.org/document/9195464/

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