Operation Parameter Optimization Analysis Of Air-conditioning Water Systems Based On Data Mining

At the 75th United Nations General Assembly,President Xi proposed the ambitious goals of carbon peaking and carbon neutrality to tackle climate change.During the operation of the central air-conditioning system,due to design margins and poor operation of the automatic control system,the energy consumption of the air-conditioning system is wasteful.As a large energy user,the optimal control and energy saving of the air-conditioning system are particularly important.With the advent of the era of big data,the application of data mining technology in various industries has become increasingly widespread.In the field of air conditioning,the role of big data mining is also becoming increasingly apparent.This paper takes the central air-conditioning system of a large public building in Wuhan as the research object.Aiming at the problems of high energy consumption of the airconditioning system and poor control effect of the existing control system,it has passed data collection,field investigation and testing,software modeling,data mining and comparative analysis.The operation of the air-conditioning system is studied by other methods.The onsite data collected covers limited working conditions,so the building load and airconditioning water system are simulated in the software.The parameters related to the operation of the air-conditioning water system are selected using the neural network algorithm.This paper uses the correlation criterion method to mine the parameters that ensure the efficient operation of the system under different working conditions.This paper selects different correlation criteria under the same boundary conditions.The example analysis shows that the operation effect of the correlation criterion with higher support and confidence is shown better.Aiming at the problem that the association criterion cannot be mined under some boundary conditions,this paper further proposes a supplementary method for the association criterion based on Euclidean distance minimization and verifies the effectiveness of the method.The results show that the correlation criterion supplemented by Euclidean distance can ensure the efficient operation of the system.This article describes the application process of association rules and simulates the operation of association rules.After that,compare them with the actual operation effect.The results show that under the optimized operation mode using the correlation criterion,the energy consumption of the water system on high load days,medium load days and low load days are reduced by 4.7%,8.8%and 18.2%respectively compared with the existing control mode.Throughout the cooling season,the power consumption of the existing mode is 281650kWh.The power consumption of the optimized operation mode is 242896kWh.The energy saving rate is 13.8%.The energy saving effect is significant.By comparing the indoor environment in the existing mode and the optimized mode,the results further show that the indoor environment is significantly improved in the optimized mode.