Research On Energy Conservation Heating Control System Of Large Public Buildings

Nowadays, with the increasing importance of energy and environmental problems,it puts forward higher requirements on the reliability and energy conservation and emission reduction of the heating industry and heating system.The basis on the characteristics of the large public buildings itself large area and high requirement on heat,the conservation of heating energy is particularly important.To fundamentally solve the problem of high energy-consumption operation in heating system of Chinese large-scale public building,and createa comfortable,healthy thermal environment of large public building with lowenergy consumption and low emissions,It has the importantly practical and social significance on promote the development of Chinese large public buildings energy conservation and emission reduction.This papers tudies the effective factors of the larges cale public building heating load, with neural network base don differential evolutional go rithmoptimization making aprediction of heating load,and design sheating area controller with heating load model of analysis.There search work is divided into the following gareas:(1)Madea statement for heating control system structure of the large public buildings in detail,on the basis of the comprehensive under standing about the heating system in the current domestic and international research status,inview of the current deficiencies in control theory and control system,it establishes the starting point of this study that the improvement of control algorithm mandoptimal control system.(2)With PMV-PPD thermal comfort evaluation index,the paper calculated the best comfort environment temperature parameters of the large public building.In order to study the building heating energy consumption problem accurately,this paper made the experiment of heating energy consumption, analyzing the influencing factors of heating load of the building in detail.(3)Based on preprocessing the experimental data, the paper made the modeling and verification by using the regression analysis method and neural network algorithm, and simulation tests were carried out by using MATLAB software. Because the neural network is easy to cause local minimum problem, the paper made the BP neural network algorithm in the optimization through differential evolutional gorithm and the establishment of rapid and accurate heating load model analyzed.(4)Because the traditional PID control lack of the effective control strategy for nonlinear system environment and related parameters of the system,the paper made the control system in the optimization through differential evolutional gorithm, there sults show that the system has characteristics of strong robustness, high control precision and response speed etc.,the paper described the design of the heating zone controller in detail, and achieve energy saving in the practical application of construction.