Research On Building Energy Conservation Control Strategies And Its Application Under The Conditions Of The Fog And Haze

For the frequent appearance of fog and haze, this paper analyzes China’s environmental and energy to face the grim situation according to authorities released economic and energy consumption data. And pointed out that energy consumption of buildings accounts for46%of the total energy consumption, this is an urgent need to solve. Especially the air conditioning and lighting energy consumption problem are particularly acute. Energy efficiency of buildings has been a worldwide trend, China’s building energy conservation work not only started late, and with the low levels. Therefore, this topic is still a frontier and applied research at home. The main research contents of this paper are as follows.For lighting energy saving problems, this paper uses intelligent control strategy based on image processing techniques to compensate for the traditional lighting control system defects, In this paper, by segmentation of images that collected by CCD image sensor, real-time access to accurate information on the target area illumination, and contrast the defaults with the obtained, and achieve accompany lighting. The core technology of this control system is selection for image segmentation algorithm, and image segmentation directly affects the subsequent feature extraction and object recognition. Particle Swarm Optimization has provided a new impetus and direction for the development of image segmentation. However, the particles’ loss of biodiversity may cause the premature convergence of the algorithm in the later of Particle Swarm Optimization.In this paper, particle swarm optimization algorithm for this problem has been improved. And paper has applied the improved algorithm in lighting multi-threshold image segmentation. Experimental results show that the improved algorithm has a higher accuracy of segmentation.VAV air-conditioning system is an energy-saving potential of the current. It characterized by changing the air supply volume instead of the indoor air temperature to meet the change in the load, and this system has been gradually applied in large public buildings.VAV air-conditioning system is a nonlinear, time-varying, large disturbance cascade control system, the traditional cascade PID controller is difficult to achieve the desired control effect, can not even guarantee the system stability. In light of few parameters of the quantum particle swarm optimization algorithm, Simple structure and fast convergence, etc., this paper presents an adaptive control strategy based on QPSO-PID. But the basic QPSO algorithm there are many problems, such as low precision, easy divergence, the algorithm does not converge and other issues, therefore, in the application need to improve and refine the algorithm. This paper points out to dynamically adjust the inertia weight based on the current evolution speed factor and quantum particle swarm and aggregation factor, so that the algorithm has a dynamic adaptability.In this paper, the intelligent lighting control system based on image processing and pressure-independent VAV air-conditioning end of the cascade control system using a simulation Matlab7.0.I have got the good simulation results, and provide theoretical basis and reference for actual building energy.