Design of energy consumption monitoring system of public buildings based on artificial neural network

Chuan He, Jin Lin, Xin Xiang, Lie Yu and Hui-hua Xiong

International Journal of Industrial and Systems Engineering, 2022, vol. 41, issue 3, 349-362

Abstract: In order to overcome the problems of low monitoring accuracy and long response time in traditional energy consumption monitoring system of public buildings, a new energy consumption monitoring system of public buildings based on artificial neural network is proposed. The system hardware is designed by using the energy consumption collection subsystem and energy consumption data transmission subsystem of public buildings. Through the genetic algorithm to optimise the constraint parameters of the physical sign extraction function to obtain the characteristics of public building energy consumption, combined with the main factors affecting the building energy consumption, the public building energy consumption monitoring model based on artificial neural network is established, and the real-time monitoring of public building energy consumption is realised through the model. The experimental results show that, compared with the traditional monitoring system, the minimum monitoring error of the designed system is only 0.01.

Keywords: artificial neural network; public building; energy consumption monitoring system; genetic algorithm. (search for similar items in EconPapers)
Date: 2022
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