Work

Energy management system design for high energy consuming enterprises integrating the Internet of Things and neural networks

Year: 2025

Type: article

Abstract: INTRODUCTION: High energy consuming enterprises continue to pay increasing attention to energy consumption. Therefore, designing an energy management system is significant.OBJECTIVES: To improve the management level and economic benefits of enterprises, a high energy consuming enterprise energy management system design based on Internet of Things technology and neural network algorithms is proposed.METHODS: Internet of Things devices are used for data collection and transmission. The combination of neural network model prediction and optimization algorithms can achieve real-time monitoring, prediction, and optimization control of energy consumption.RESULTS: The research results indicated that the response time of the high energy consuming enterprise energy management system proposed in the study was 80.2 ms when the number of people was 600. The fluctuation range of CPU usage within 24 hours was 14% to 45%.CONCLUSION: A high energy consuming enterprise energy management system that integrates the Internet of Things and neural networks can manage energy more efficiently and intelligently, thereby improving the production efficiency and economic benefits of the enterprise. This helps companies gain greater advantages in fierce market competition.

Source: EAI Endorsed Transactions on Energy Web

DOI: 10.4108/ew.4849

Authors: Zhaolin Wang, Zhiping Zhang

Institution: Chongqing College of Finance and Economics

Language: English

Topic: Energy Efficiency and Management

Subfield: Renewable Energy, Sustainability and the Environment

Field: Energy

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy

Open Access status: diamond

Funder: Chongqing Municipal Education Commission