Research On Large Space Environment Optimization Control Based On PMV Index

With the rapid development and progress of the social economy,people have put forward higher requirements for the air quality in the building interior.The effect of the air-conditioning hot and humid environment has become the focus of attention.At present,air conditioning control systems have disadvantages such as poor comfort and high energy consumption when providing services for people’s lives.Traditional control strategies aiming at temperature and humidity are no longer satisfactory.People’s requirements for comfort.Based on the analysis of the domestic and international research status,this paper proposes an environmental optimization control method based on PMV index.This method predicts the indoor PMV index in real time through GA-BP prediction model.Relevant valve mechanism to adjust the thermal comfort of the indoor environment.The main tasks completed are as follows:1.Quantitative analysis of factors affecting PMV indicators.Through field research on the status quo of air conditioning control of large office buildings,comparing the current evaluation methods of several thermal comfort indicators,the PMV thermal comfort index is finally determined as the evaluation standard of this paper.On this basis,the theoretical basis and influencing factors of human thermal comfort are analyzed.The MATLAB software quantitatively gives the influence of various environmental factors on the selected indicators,and determines the control strategy based on the influence degree of the relevant environmental parameters on the PMV indicators.2.Research on predictive model of thermal comfort index PMV.Aiming at theproblems that the previous scholars used a single neural network to construct a PMV prediction model with random initial network weight threshold,the prediction result is easy to fall into the local minimum,and the prediction model has low precision,a PMV index prediction model combining genetic algorithm and neural network is proposed.The model uses genetic algorithm to quickly optimize the initial weight and threshold of BP neural network.The experimental simulation shows that the model has good prediction effect.3.Design and simulation of fuzzy PID controller for thermal comfort of air conditioning system.The design steps and design points of the fuzzy controller are established.According to the professional experience and experimental analysis,the relationship between e,ec and PID regulators is summarized and fuzzy rules are constructed.The fuzzy PID control system based on thermal comfort index is established by Simulink simulation tool,and the control system is simulated.Finally,the control effect is compared with the traditional PID.The results show that the fuzzy PID control effect is better than the traditional PID.By operating under different working conditions,not only energy consumption is reduced,energy saving of air conditioning system is realized,but also air conditioning system is improved.The comfort and environmental quality of the system have a certain influence on the traditional air-conditioning method of controlling indoor temperature and humidity.