Prediction method of energy efficiency ratio of central air-conditioning operation based on extreme learning machine

Abstract

On the premise of accurate prediction of the energy efficiency ratio of the water system of the central air-conditioning unit, the research on the optimization and control of the central air-conditioning system can be better realized. Aiming at the characteristics of high data dimension and large data volume of central air-conditioning unit equipment, a central air-conditioning energy efficiency ratio prediction method based on extreme learning machine is proposed, which can effectively help the energy-saving research of central air-conditioning system. This paper selects the operating data of the central air-conditioning system of a large building, constructs an extreme learning machine data set, builds an extreme learning machine model through the training data set, and determines the optimal number of hidden layer nodes; then uses the test data set and different extreme learning machine models to predict The results are compared, and the number of hidden nodes in the prediction model of the extreme learning machine with the best performance is obtained.