A review from design to control of solar systems for supplying heat in industrial process applications. (July 2022) - Gil, Juan D.; Topa, A.; Álvarez, J.D.; Torres, J.L.; Pérez, M.
Abstract: The use of solar thermal systems to produce heat for industrial processes is a feasible option that is gaining increasing interest in recent years as an initiative toward the zero-carbon energy future. This technology has a place in different processes, yet there is still no consensus on the main methods for sizing or controlling. The design requires the use of specific techniques due to the inconstant nature of solar energy as well as the heterogeneity of some industrial thermal demands. Nevertheless, despite starting from a particular system's design, the dynamic together with the hybrid and nonlinear behavior of the processes involved require adequate control techniques to provide the energy in a usable form and keep the system operating close to the design specifications. This paper presents a literature review concerning research works that address the design and control of solar thermal systems used in industrial contexts. The main objective is to analyze the different techniques used and to highlight their limits, usefulness, and the various industrial sectors where they were applied. The results of this analysis can be seen as a decision-making tool to select the most appropriate design or control strategy for these applications. It has been found that control techniques such as model predictive control can improve key performance metrics in daily operation. However, further development on these kinds of techniques and in holistic optimization methods that exploit the synergies between the operational and design phases is required. Highlights: Design and control methods for solar thermal systems used in industries are reviewed. The barriers and usefulness of each technique identified are analyzed. The analysis results in a decision-making tool to select the most appropriate method. Optimization-based design outperforms the other techniques for heterogeneous demands. Advanced controllers can play a role due to the nonlinear system's behavior.