Selection and Evaluation of influencing Parameters for Heat Load Forecasting Model

This paper analyses the factors affecting heating consumption of a substation. The input parameters neural network prediction model are analysed and selected. average absolute error, percentage mean square error used to evaluate effect model. results show that when maximum outdoor temperature, temperature difference between primary supply return domestic hot water, load in previous three days, two day minimum day, effects better.