Research On Sun-tracking Control And Concentrating Strategy Of Tower Heliostats

Heliostats are the primary component of energy transfer in tower CSP station.Their functions are to track,reflect,and accurately focus sunlight on the heat sink on the top of the heat collection tower.Therefore,the heliostat tracking control technology is one of the key technologies of tower CSP station.Because of the mechanical errors of the heliostat and external factors,the tracking error of the heliostat increases during the operation,which causes the light-to-heat conversion efficiency of the power station to decrease and directly affects the power generation efficiency of the power station.Therefore,this paper is mainly aimed at the research and implementation of the heliostat reflection spot detection and the heliostat reflection spot deviation correction in the process of sun-tracking control of the heliostat of the heliostats field in the tower CSP station to reduce the tracking error of the heliostat,its main tasks as follows:(1)Consult domestic and foreign literature to understand the influence of the heliostat tracking control on power generation efficiency and the research status of the heliostat tracking control system in tower CSP station.By studying the law of solar motion and analyzing the principle of the heliostat sun-reflection,a sun-tracking model of the heliostat is established and the rationality of the model was verified by simulation.(2)Based on the analysis of the error factors of the heliostat and the advantages and disadvantages of the existing heliostat tracking control methods,an improved scheme based on open-loop tracking control combined with 3D electronic compass real-time measurement of the heliostat tracking attitude as closed loop feedback is proposed.The design of open and closed loop tracking control system is completed and the heliostat device is built.(3)The influence of the heliostat reflection spot on the light collection efficiency of tower system is analyzed,and a heliostat reflection spot detection method based on Beam Characterization System is proposed.A Beam Characterization System is established and a heliostat focusing experiment is designed to collect light spot images at different times of the day,and through image processing and calculation,the image spot deviation and actual spot deviation data are obtained.At the same time,a heliostat reflection deviation model is established based on Euler’s rotation matrix principle to realize the conversion of the heliostat reflection spot deviation to the heliostat angle error.(4)The prediction results of spot deviation data of each algorithm are compared and analyzed,and a correction method of the heliostat reflection spot deviation based on the improved Extreme Learning Machine algorithm is proposed.Based on the inputoutput model constructed by the improved Extreme Learning Machine algorithm to predict the spot deviation data,combined with the analysis of the tracking process of the heliostat,the correction model of the heliostat reflection spot deviation is established and applied to the heliostat focusing experiment.The experimental calculation shows that the tracking error of the heliostat in the three days after correction is 5.775 milliradians,which is 34.1% lower than that before the correction,which proves the feasibility of the correction of the heliostat reflection spot deviation based on the improved Extreme Learning Machine algorithm.