Validation of a closed-loop aim point management system at the Jülich solar tower

Abstract

Due to modeling errors and disturbances caused by clouds, Solar Power Tower (SPT) plants consider high safety margins during operation leading to a significant loss of revenues. This conservatism contradicts the expansion of SPT plants despite their potential. In this work, an aim point management system is deployed at the open-volumetric receiver of the Jülich solar tower. It employs All Sky Imager (ASI)-based nowcasts as well as flux density and temperature measurements. While the temperature measurements provide feedback for an outer receiver control loop, the flux density measurements offer feedback for an inner heliostat field control loop of a cascade control. The receiver controller estimates flux density setpoints for the inner control loop. By comparing these flux density setpoints with measured flux densities, a static optimal control technique compensates for modeling errors and increases the intercept. This control requires a fast aim point optimization, the enhanced ant-colony optimization meta-heuristic. Furthermore, a feed forward controller compensates for disturbances due to clouds by scaling the heliostats’ reflected power used in the system model by DNI nowcasts. At the Jülich solar tower, the static optimal control compensates for changes in the allowable flux density in less than three control steps. The cascade control controls the subreceivers in a narrow temperature range of 15K, which has never been achieved before at this tower.