Research On Energy Saving Control Of Central Air-conditioning Refrigeration Station System Based On Load Forecast

With the increasing demand for environmental comfort,the use of air conditioning systems has become inseparable from people’s lives.In China,the energy consumption of central air conditioning systems accounts for about 40% of the total energy consumption in the construction industry.As the core of the central air conditioning system,the refrigeration station system has many kinds of equipment and heat exchange links.The refrigeration station system has the characteristics of large delay,multi coupling,time-varying and strong nonlinearity,which makes the energy conservation research of the refrigeration station system complex,and it is difficult to carry out optimal control.Therefore,this article takes the central air conditioning refrigeration station system as the object,and optimizes and controls the refrigeration station system by predicting the load of the central air conditioning system,in order to achieve energy-saving and stable operation of the central air conditioning refrigeration station system.This article mainly conducted the following research:Firstly,this article introduces the working principle of the central air conditioning and refrigeration station system,as well as the main equipment composition and operation mode of the refrigeration station system.Analyzed the energy-saving principle of variable flow control,and introduced the operation strategy of variable flow operation for the chilled water system and cooling water system.Finally,a simulation model of the experimental platform was built based on TRNSYS and simulated.Secondly,this article analyzes and identifies the main influencing factors on the cooling load of central air conditioning.Based on Extreme Learning Machine(ELM),a central air conditioning cooling load prediction model is established,and the input parameters of the model are determined based on the analysis of the influencing factors of central air conditioning cooling load.A fusion multi strategy improved Whale Optimization Algorithm(IWOA)was proposed to optimize the input weight matrix and hidden layer threshold of ELM.The improved IWOA ELM model significantly improved the accuracy of air conditioning load prediction compared to the pre improvement and post improvement models.Thirdly,the energy consumption models of chillers,cooling water pumps,chilled water pumps,and cooling tower fans were fitted using the least squares method,and their respective constraint conditions were determined to establish the energy consumption model of the refrigeration station system.Based on the actual load demand,the IWOA algorithm proposed in this article was used to optimize the operating parameters of the refrigeration station system,obtain the optimal energy consumption value of the refrigeration station system,and determine the operating parameter values under the minimum energy consumption of the refrigeration station system.Finally,aiming at the control problem of water flow and outlet temperature of cooling tower in the refrigeration station system,the frequency flow control model of pump and the frequency outlet temperature control model of cooling tower fan are established by using the system identification method.A flow control scheme based on IWOA PID is proposed to address the characteristics of small delay and fast response in the frequency flow model of water pumps.A cooling tower outlet temperature control scheme based on IWOA optimized model free adaptive control(MFAC)is proposed to address the characteristics of large delay and strong nonlinearity in the frequency outlet temperature control model of the cooling tower fan.This achieves optimal control of the refrigeration station system.