Study On Energy Consumption Modeling, Analysis And Energy-saving Strategy For VAV Central Air Conditioning

Energy has been considered as one of the most crucial elements for human society, especially to those countries which contain large amount of populations but without corresponding amount of energy. Take China as an example. To realize the sustainable development in both economic and society, China has to consider economizing energy in every way. As modernization has step by step deeply swept across all over the country, the problem of enormous energy consumption that brought by running the public infrastructure is bothering China seriously. And 50% ~ 60% among of such energy consumption is contributed by the air conditioning. Therefore, to save more energy, focusing on investigation and research in improving the energy consumption system of air conditioning should be the indispensable business that needs to be conducted by the related institutes in China.The Variable Air Volume is the system that used to adapt the indoor temporary through controlling the rate of flow of the air. And it has been applied widely due to its superb ability for energy consumption. Based on such concept, this article would display the further research on energy consumption for the Variable Air Volume system. Firstly, the article will present the different control ways for Variable Air Volume. With the help of the research accomplishment of the Variable Air Volume system by xiaan architecture and Technology University, as well as using vomron plc and LabVIEW, we have realized the integration of the software and hardware, also completed compiling for some of the programs. Secondly, the article would demonstrate the features of energy consumption devices by analyzing energy consumption of each part of the Variable Air Volume system. Also, with the help of WebAccess configuration software that made by the Advantech company in Taiwan and building management system that designed by the BEMS, the Central Variable Air Volume measuring and analyzing system has been installed. And this system also has been tested through experiments. Finally, this article would show that we achieve superb fitting degree through building the neural networks model to the energy consumption of the fan by application of the BP and RBF. In addition, aiming at the ventilating temperature which is one of the main elements that affecting the energy consumption of the fan,we optimized the controller by The fuzzy adaptive PID,and this also achieved satisfactory result for system control.