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Abstract: The global shift toward distributed energy resources (DERs) has accelerated the deployment of microgrids (MGs)…
The integration of autonomous robots with intelligent electrical systems introduces complex energy management challenges…
Given the urgent need to enhance the resilience of microgrids under extreme weather conditions and the limitations in ad…
In-depth exploration of reinforcement learning algorithms applied to various microgrid architectures. Identification of …
Deep Reinforcement Learning (DRL), a subset of artificial intelligence, holds the potential to revolutionize the control…
In [10] offered A fuzzy Q learning method based on genetic algorithms for energy management in smart grids and in [11] o…
This paper investigates the performance of a grid-connected inverter in a hybrid microgrid and compares different contro…
This article provides systematic review to follow a thorough evaluation of the present status of research on reinforceme…
This study presents a simulation-based and adaptive reinforcement learning (RL)-based energy management framework that a…
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