Research on Industry 4.0 smart grid monitoring and energy management based on data mining and Internet of Things technology

Abstract

With the increasing global focus on sustainability and energy efficiency, the concept of Industry 4.0 is becoming an important driver of smart grid technology advancement. Traditional power grids are faced with the challenges of high energy consumption and low management efficiency, and it is urgent to realize intelligent transformation through emerging technologies. This study aims to explore the application of data mining and Internet of Things technology in smart grid monitoring and energy management, with a particular focus on thermal energy management, in order to improve energy utilization efficiency and achieve dynamic regulation. A smart grid monitoring platform integrating data mining and Internet of Things technology is constructed. The data of power and heat energy are collected by sensors, and the data mining algorithm is used to analyze the energy consumption behavior of users and the running state of equipment. A prediction model is also introduced to realize dynamic prediction and optimal scheduling of heat demand. The experimental results show that the thermal energy management system based on the platform can significantly improve the energy utilization rate, data mining technology effectively identifies the peak energy use and potential energy saving opportunities, and the Internet of Things technology realizes real-time monitoring and feedback, enhancing the flexibility and response ability of the system. Through accurate energy monitoring and effective management strategies, it can not only realize the optimal allocation of resources, but also promote the development of enterprises in the direction of low-carbon environmental protection.