| Saving is one of the significant problems which the current social is development, and on building energy saving is one of the important fields. In large-scale public buildings, air-conditioning electricity energy accounted for about 50%-60% of the whole building energy consumption, therefore improving national energy saving consciousness, the improvement and optimization of the air conditioning control strategy can achieve good energy saving effect. With the development of technology, variable air volume (VAV) air-conditioning system which it has the potential saving energy has been widely used.Because HVAC system is designed by its peak load, and air-conditioning system is run under partial load most of the time, so we must improve the performance of the control system, and reduce the air-conditioning system energy consumption. This paper firstly introduces the control method of VAV air conditioning system, each of the equipment operation characteristics and energy consumption characteristics are analyzed. Adopting the researching platform of The Intelligent Building Environment Laboratory in Xi'an University of Architecture and Technology, energy consumption and charging system hardware and software basing on the hardware and using Labview programming language have been figured out, it can real-time measure the power consumption of the equipment, and it can truly collect the charge of the individual room. Secondly, using RBF neural network to the air flow output of air conditioning system on the soft measurement, the sensor can be dynamical monitoring air conditioning, and realize air parameters estimation when the sensor is breakdown. Finally, we apply fuzzy immune PID algorithm to optimize supply air temperature control system, the simulation results show that, compared with the PID algorithm it has better control effect.
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