In this study, Online Home Energy Management Systems (ON-HEM) using Q-Learning and DQL are proposed. The proposed system consists of power resources (grid, PV), ...
Jun 1, 2024 · The findings demonstrate both the superiority of DQL over Q-Learning and the efficiency of the proposed ON-HEM in decreasing high peak demand, ...
This paper presents a hybrid energy management method that utilizes the Deep Deterministic Policy Gradient (DDPG) algorithm. To enhance its exploration ...
Jun 1, 2024 · The proposed SV2G-ET scheme employs a deep Q-network for EVs scheduling for charging/discharging. SV2G-ET scheme uses InterPlanetary File System ...
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This resulted in this research paper, which aimed to apply deep reinforcement learning algorithms for an autonomous energy management system of a microgrid.
In this paper, we introduce three different Deep Reinforcement Learning (DRL) algorithms to minimize the operational cost in the long run and keep the battery ...
The proposed Q-learning home energy management algorithm, integrated with the artificial neural network model, reduces the consumer electricity bill within the ...
An evolution algorithm Grey Wolf Optimizer based on the swarm intelligence is applied to manage the energy storage system by charging the battery when the ...
Sep 14, 2022 · Reinforcement Learning is a class of machine learning algorithms that is making deep inroads in various applications in energy management in ...
This article investigates an energy cost minimization problem for a smart home in the absence of a building thermal dynamics model