| Solar-thermal reactors represent a promising alternative to fossil fuels because they can harvest solar energy and transform it into storable and transportable fuels. The operation of solar-thermal reactors is restricted by the available sunlight and its inherently transient behavior, which affects the performance of the reactors and limits their efficiency. Before solar-thermal reactors can become commercially viable, they need to be able to maintain a continuous high-performance operation, even in the presence of passing clouds. A well-designed control system can preserve product quality and maintain stable product compositions, resulting in a more efficient and cost-effective operation, which can ultimately lead to scale-up and commercialization of solar thermochemical technologies.;In this work, we propose a model predictive control (MPC) system for a solar-thermal reactor for the steam-gasification of biomass. The proposed controller aims at rejecting the disturbances in solar irradiation caused by the presence of clouds. A first-principles dynamic model of the process was developed. The model was used to study the dynamic responses of the process variables and to identify a linear time-invariant model used in the MPC algorithm. To provide an estimation of the disturbances for the control algorithm, a one-minute-ahead direct normal irradiance (DNI) predictor was developed. The proposed predictor utilizes information obtained through the analysis of sky images, in combination with current atmospheric measurements, to produce the DNI forecast.;In the end, a robust controller was designed capable of rejecting disturbances within the operating region. Extensive simulation experiments showed that the controller outperforms a finely-tuned multi-loop feedback control strategy. The results obtained suggest that our controller is suitable for practical implementation. |
