Solar thermal systems are inherently required to deal with large fluctuations in solar radiation. Dealing with these fluctuations accurately has a significant impact on the lifetime of the system components and the overall system performance. This project seeks to bring the methodology of model predictive control (MPC) to the concentrating solar technology (CST) field. The overall goal is to use advanced control to produce more reliable and better-performing CST systems. The intended focus areas of the project are:

1. The formulation of dynamic models of solar thermal processes which are suitable for MPC algorithms.
2. The development of model predictive controllers and estimators based on existing and newly developed solar thermal process models.
3. The development of image based cloud tracking systems that can forecast cloud cover over large spatially-distributed solar thermal fields/arrays.
4. Supervisory control strategies for solar thermal plants that consist of multiple connected receivers/reactors.