Analysis on Influencing Parameters of Heating Consumption Prediction

School of Environment and Energy Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China

^* Corresponding author’s e-mail: lirui@bucea.edu.cn

Abstract

This paper studies the influencing parameters of the heating consumption prediction in heating substation, uses the BP neural network to predict the heating consumption, and establishes four BP neural network structures to change the outdoor average temperature, the lowest temperature and the highest outdoor temperature, the predicted results found that when the input variables include the average outdoor temperature, the lowest outdoor temperature, the highest outdoor temperature, the wind speed, and the heating consumption of the previous three days, the prediction results are better , the relative error is equal or less than 0.25%.