Research On Improved Control Method For Central Air-conditioning Energy Saving System

With the development of science and technology, central air-conditioning system has been widely used in high-rise buildings, while the energy cost by central air conditioners in these buildings accounts for up to 45% of the total energy consumption, which inevitably leads to a high running cost. To significantly reduce the energy consumption of central air conditioning system, the application of frequency control technology is trend, as well as the intelligent control method, should be used comprehensively to achieve a better control effect.The thesis firstly introduces the structural characteristics of central air-conditioning system and its working principle, as well as the energy consumption. Combined with the People’s Hospital of Baodi project for instance, we design a central air-conditioning energy control system. Critical techniques and the control principles are introduced in the thesis. By analyzing the monitoring data, the fact that using variable frequency speed regulation technology can reduce the energy consumption of the air conditioning system is verified.Secondly, as the conventional PID control method has the defect of a long regulation time with a large amount of overshoot, it is difficult for the system obtain a satisfactory control effect. Thus fuzzy PID controller is applied to central air conditioning system in this thesis. By using the mechanism analysis method, the mathematical model of controlled object is constructed, and fuzzy PID controller is designed. We use Matlab/Simulink method to establish the model of fuzzy PID controller and the conventional PID controller, and by implementing the simulation experiments and comparing the response curves of each situation, we verified that fuzzy PID controller has a better performance in adjusting time, overshoot and system stability.Finally, in order to improve the control effect of fuzzy PID controller further, chaos ant colony algorithm is applied to optimize the quantization factor and scaling factor of fuzzy controller in the thesis, which will overcome the subjectivity of fuzzy controller parameter settings. Relative simulation experiments are conducted at the end of the thesis, and the results of the experiments show that the control effect of fuzzy PID controller with a chaos ant colony optimization possesses a better control effect in the central air conditioning system.