Predicting the Air-conditioning Load under Drought Conditions Based on ELM

In this paper, a model based on ELM is proposed to predict the air-conditioning load under drought conditions by analyzing the daily average air-conditioning load during the drought. The main meteorological factors that impact the air-conditioning load are considered in the model, and then the air-conditioning load under drought conditions can be predicted by training the samples by the single hidden layer feed forward neural network of ELM. Thus, the model is used to provide good theoretical basis for management on the demand side of power sector. Finally, an example is showed to prove that the curve of the air-conditioning load forecasting model and the curve of the actual cooling load of the power are almost consistent, and the prediction is accurate, reliable, and can be applied to other load forecasting.