Building Load Prediction and HVAC System Operation Optimization based on Artificial Neural Network
Accurate building load prediction and operation optimization of the heating,ventilation and air-conditioning(HVAC)system are important for improving the economic performance and energy efficiency of the HAVC system.The building load prediction model is established by using artificial neural network.Thermal comfort demands of occupants in different thermal zones are considered to improve the prediction accuracy.Aiming at the lowest operation cost of air conditioning system,the operation optimization model of ground source heat pump system combined with thermal storage tank is established by using genetic algorithm.The results show that the CV-RMSE of the prediction model can decrease by 15.26%.Based on the load prediction results,the optimization model realizes that the operation scheduling of the HVAC system can save operation cost by 22.53%and 33.69%on typical winter days and typical summer day,respectively.
万方数据
维普
