This article explored the application of smart energy management in the green Internet of Things (IoT), with the goal of improving energy utilization efficiency and achieving energy conservation and emission reduction...
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ISBN:
(纸本)9798400718144
This article explored the application of smart energy management in the green Internet of Things (IoT), with the goal of improving energy utilization efficiency and achieving energy conservation and emission reduction. Through analysis of existing research, it was found that traditional energy management methods had many shortcomings in real-time monitoring, data processing speed, and intelligence level. To address these issues, this article proposed an intelligent energy management method based on the DRL (Deep Reinforcement Learning) algorithm. Based on the DRL algorithm, the average energy consumption was 11.5 kWh. Secondly, in terms of device collaboration capability, the DRL algorithm significantly reduced data transmission latency. In the final reliability evaluation of intelligent energy management system based on DRL algorithm, the average recovery time of DRL algorithm was 40 seconds, and the average task completion rate was 90.2%. From the data conclusion, it can be seen that the intelligent energy management system based on DRL algorithm has significant advantages in improving energy utilization efficiency, optimizing equipment collaboration ability, and enhancing system reliability.
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