Design of aiming control strategies to enhance energy harnessing in power-generation solar systems with central receiver during cloud shading transients
Alternative technologies that have the potential to replace those based on non-renewable resources still need to grow. One of the most promising technologies is central solar towers. In central-tower thermal power plants, an array of large mirrors called heliostats redirects the solar radiation towards a receiver located at the top of a tower. Then a heat transfer fluid flowing through the receiver takes the concentrated radiation and transports the heat to a conventional thermodynamic cycle to generate power. However, at ground level, direct solar radiation mainly varies because of clouds, which is a complex phenomenon not easily predictable. This solar radiation transient variation can cause dangerous high thermal stresses over the central receiver, an unwanted condition due to the cost of these kind of devices. This dissertation proposes a novel closed loop heliostat aiming point strategy based on a multiple-input-multiple-output model predictive control (MPC) approach to maintain safe operating conditions even when the system is under the effect of solar radiation disturbances. The results reveal that the primary feedback loop aiming strategy could successfully restore the solar receiver back to its steady state after transient operations caused by clouds. However, the controlled variables showed undesired overshoots and high heating rates. These issues are overcome through a set point readjustment approach, which is temporally supported by a PI controller. Following tests indicate that the proposed aiming control strategy provides a continuous safe operation of the solar central receiver when subject to transient flux distribution due to clouds
