Microgrid energy management using deep Q-network reinforcement learning

Microgrid energy management using deep Q-network reinforcement learning

This paper proposes a deep reinforcement learning-based approach to optimally manage the different energy resources within a microgrid. The proposed methodology considers the stochastic behavior of the main elements, which include load profile, generation profile, and pricing signals. The energy man...

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Bibliographic Details
Main Authors: Mohammed H. Alabdullah, Mohammad A. Abido
Format: Article
Language:English
Published: Elsevier 2022-11-01
Series:Alexandria Engineering Journal
Subjects:
Deep reinforcement learning
Deep Q-networks
Energy management
Microgrid
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016822001284

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http://www.sciencedirect.com/science/article/pii/S1110016822001284

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