Research On The Key Technology Of High Precision Sun Position Tracking

High precision solar tracking technology is particularly important to improve the efficiency of solar thermal power generation.At present,the sun tracking accuracy is restricted by the following two problems: one is the accuracy of the sun position detection for closed-loop motion control;the other is the inherent systematic error of the sun tracking device.This dissertation focuses on the researches of high precision sun position detection and the system error analysis and compensation of sun tracking device,which are of great significance for improving the sun tracking accuracy.In this dissertation,the image detection method is used to improve the accuracy of the sun position detection in the sun tracking system.Firstly,the high resolution image sensor is used to obtain the sun image.Secondly,mean filtering,histogram bimodal segmentation and ‘Canny’ edge detection are used to get the solar edge points in the image.Thirdly,two algorithms for detecting solar spot center are designed.In the experiment,the average error of the arc detection algorithm based on frequency distribution used to detect simulated cloudy images is 0.325’ and the maximum error is 1.08’.The average error and maximum error of the arc detection algorithm based on the maximum fit are 0.715’ and 1.775’,respectively.Based on this result,the dissertation selects the arc detection algorithm based on frequency distribution with higher accuracy as the final algorithm for solar position detection,and the experimental results with solar image data meet the expectations.The results show that this algorithm can effectively solve the problem of spot center detection in cloudy weather,and has certain theoretical and practical significance for high-precision sun position detection.For the problem of systematic errors in the biaxial tracking system,this dissertation established a kinematics model of the biaxial tracking system based on D-H parameter method and coordinate transformation method,and used MATLAB to analyze the influence of the deviation direction of the mirror normal,pitching axis and azimuth axis from the ideal position and the comprehensive random errors of the three factors on the system tracking.Finally,the particle swarm optimization algorithm is used to compensate the system error.The results show that the tracking error of the system is related to the tilt of the mirror normal,pitch axis and azimuth axis,and the error generally changes with time.When the system synthesis error is given randomly,the tracking error usually changes rapidly at noon and slowly at other times.Particle swarm optimization algorithm and kinematics model can effectively solve the problem of error compensation,which has certain theoretical value for improving the accuracy of the solar tracking system.