With the development and progress of society, people have higher and higher requirements for indoor high temperature and humidity environment. The traditional air conditioning system uses temperature and humidity as control parameters, which has a single control goal, low comfort, and high energy consumption. The purpose of this study is to use predicted mean vote (PMV) thermal comfort index and green building to analyze the intelligent control system of indoor environment. Our intelligent research platform is a set of “intelligent” experimental platforms. The sample data were divided into human metabolic rate, human external work, and heat resistance of clothes, temperature, and air. According to the PMV value, velocity, relative humidity, and average radiation temperature are divided into three categories, which are composed of seven parameters. According to the survey results, PMV at 24°C fluctuates around 0.5, which is an important value for human thermal comfort, and people will feel more comfortable. When the temperature reaches 26°C, the PMV index will reach 0.6 or even more than 0.6, and the human body will be in an unpleasant state due to overheating. In addition, the higher the wind speed is, the smaller the PMV value is and the stronger the cooling effect is. The higher the temperature is, the smaller the influence of wind speed on PMV value is. In other words, the sensitivity of the human body to wind speed will be reduced. In this study, the PMV index intelligent control system can adjust the indoor environment properly, and the conclusion is that the energy consumption and use effect are superior to air conditioning equipment. This research has contributed to the development of intelligent buildings.
Research and application of an intelligent control system in central air-conditioning based on energy consumption simulation
