The Power Consumption Model of Chiller with Elman Neural Networks for On-line Prediction and Control
In this paper, a new steady-state power consumption model using the Elman Neural Network (ENN) is proposed. The model is dependent on the external parameters of chiller, which are easily monitored and which are related to the global optimization of an air-conditioning water system. The simulation results show that the model can complete the training process within 3 s. In addition, it can be seen that the results of the model are in good agreement with the experimental values with the majority of the RE values within ±3%. Therefore, this model is suitable for on-line prediction of the power consumption of chiller in on-field engineering.
KeywordsElman neural network On-Line prediction Chiller Global optimization Power consumption
The work is supported by National Key Research and Development Project of China (Grant No. 2017YFC0704100, entitled “New Generation Intelligent Building Platform Techniques”) and “the Fundamental Research Funds for the Central Universities” (Grant No. DUT17ZD232).
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