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...
Main Authors: | Mohammed H. Alabdullah, Mohammad A. Abido |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2022-11-01
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Series: | Alexandria Engineering Journal |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016822001284 |
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