Real-time prediction of sub-item building energy consumption based on PCA-AR-BP method

In this paper, a new method for real-time prediction of building energy consumption is proposed, this method solves the problem that the kinds of energy consumption are not distinguished and the prediction accuracy is low in the current energy consumption prediction algorithms. This paper divides the total energy consumption into four sections. Firstly, three main influencing factors of building energy consumption are extracted using PCA to realize real-time prediction; Secondly, the method of lighting energy consumption prediction based on time series analysis is constructed, the lighting energy consumption of the building is predicted in real time. Finally, the energy consumption prediction model based on BP network is established to predict the air conditioning, power and special energy consumption of the building. The experimental results show that the prediction model can predict energy consumption in every part of a building more accurately and effectively. (paper)