Prediction of heating energy consumption in university building based on simplified artificial neural networks

Abstract

In this paper, the main objective is to predict heating energy consumption using a simple artificial neural network. For training and testing the network daily consumption for NTNU University campus Gløshaugen and mean outside temperatures were used. Training of the network was performed by using Levenberg–Marquardt (LM) feed-forward backpropagation algorithms. Different indices of the prediction accuracy were calculated for training and testing. Simplified model showed that it can predict heating consumption with adequate accuracy. Creating a model of energy use helps in future building planning; it can provide useful information about most probable energy consumption for similar buildings, or predict energy use in different conditions.