Abstract

Abstract This paper mainly studies the energy consumption of air conditioning and refrigeration system from the perspective of the dynamic operation of air conditioning systems and selects the energy consumption of a chiller system, cooling tower system, chilled water pump system and fan coil system, which affect the energy consumption of air conditioning system, as model variables. An integrated learning method based on a multilayer perceptron is proposed to integrate spatial features with temporal features, and a spatio-temporal prediction model for air conditioning energy consumption analysis is established under the Seq2Seq framework, and then the input curves of the four variables with load change under the optimal operation of the air conditioning system under dynamic load are derived. The results show that the deviation between the simulated value and the measured, calculated value of the energy consumption analysis model of air conditioning and refrigeration equipment based on the multilayer perceptron is within 5%, which can effectively and accurately predict and reduce air conditioning energy consumption by 15% to 20%. The maximum energy-saving efficiency can reach 30% when the air conditioning system is in optimal operation under dynamic load, and the energy-saving effect of the chiller, chilled water pump and cooling water pump is relatively significant. The research results of this paper have a certain reference value for reducing the energy consumption of air conditioning systems in practice.

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