Application of artificial intelligence algorithms in the prediction of heating load

Prediction of heating and cooling load demand of user-side accurately can guide system operation and obtain economic operation strategy. Taking an energy station as the research object, the outdoor dry bulb temperature, load value, the D-value temperature of supply and return water and water supply flow at time T-1 and T-2 were selected as input parameters, and the load value at time T was selected as output parameters, the heating load prediction model based on intelligent algorithm is established. The results show that, GA-SVM and PSO-SVM algorithm can obtain higher prediction accuracy, while PSO-BP algorithm has a slightly worse forecasting accuracy.