It has great significance to estimate the schedulable capacity of air-conditioning load of public building for
participating the power network regulation by forecasting the air-conditioning load accurately. A novel forecast method
considering the accumulated temperature effect is proposed in this paper based on Elman neural network. Firstly, the
starting and ending date for forecast considering the accumulated temperature effect are determined by providing the five
day sliding average thermometer algorithm which is usually adopted in aerology research. Then, the effective
accumulated temperature of each day is calculated. Finally, take the effective accumulated temperature, temperature and
humidity into consideration, the air-conditioning load of public building in the forecast day is acquired by Elman neural
network. Simulated results show that the higher forecast accuracy can be achieved by considering the accumulated
temperature effect.
