Precise sun-tracking control of heliostats based on a sun´s image reference system

Solar tower power plant is the widest market prospect type in large-scale solar power plants during the next decades. Heliostats are the most important components in this system. To solve the problems in the sun-tracking, concentrating control and low dynamic precision of the heliostat clusters system, the nonlinear kinematical model of a heliostat is developed based on analysis of the two-axis rotation sun-tracking mechanism and property. The motion trajectory information of a single heliostat is sampled by using a sun´s image reference system combined with machine vision-based method. Nonlinear optimization is proposed to get the best sun´s image fitting to achieve the heliostat model parameters automatic intelligent calibration, which overcome the sun-tracking and concentrating precision drift caused by mechanical wears of the heliostat, the environmental and seasonal variations and achieve the high focusing rate and high efficiency of the energy collecting of the large-scale heliostat clusters. The effectiveness of proposed modeling, calibration, and control theory of heliostats are verified through theoretical simulation and experimental researches.