Solar Field Output Temperature Optimization Using a MILP Algorithm and a 0D Model in the Case of a Hybrid Concentrated Solar Thermal Power Plant for SHIP Applications

Abstract

Using solar power for industrial process heat is an increasing trend to fight against climate change thanks to renewable heat. Process heat demand and solar flux can both present intermittency issues in industrial systems, therefore solar systems with storage introduce a degree of freedom on which optimization, on a mathematical basis, can be performed. As the efficiency of solar thermal receivers varies as a function of temperature and solar flux, it seems natural to consider an optimization on the operating temperature of the solar field. In this paper, a Mixed Integer Linear Programming (MILP) algorithm is developed to optimize the operating temperature in a system consisting of a concentrated solar thermal field with storage, hybridized with a boiler. The MILP algorithm optimizes the control trajectory on a time horizon of 48 h in order to minimize boiler use. Objective function corresponds to the boiler use, for completion of the heat from the solar field, whereas the linear constraints are a simplified representation of the system. The solar field mass flow rate is the optimization variable which is directly linked to the outlet temperature of the solar field. The control trajectory consists of the solar field mass flow rate and outlet temperature, along with the auxiliary mass flow rate going directly to the boiler. The control trajectory is then injected in a 0D model of the plant which performs more detailed calculations. For the purpose of the study, a Linear Fresnel system is investigated, with generic heat demand curves and constant temperature demand. The value of the developed algorithm is compared with two other control approaches: one operating at the nominal solar field output temperature, and the other one operating at the actual demand mass flow rate. Finally, a case study and a sensitivity analysis are presented. The MILP’s control shows to be more performant, up to a relative increase of the annual solar fraction of 4% at 350 °C process temperature. Novelty of this work resides in the MILP optimization of temperature levels presenting high non-linearities, applied to a solar thermal system with storage for process heat applications.

Renewable Thermal Energy Systems: Modeling Developments and Future Directions (Report 3)

“…Hybrid plant sizing is also more sophisticated to simultaneously hit the power and temperature output targets while having coupled subsystem controls. The mixed integer linear programming algorithm is one of the proven methods to optimize the operating temperature in a system consisting of a concentrating solar thermal field with thermal storage, hybridized with a natural gas boiler (Kamerling, Vuillerme, and Rodat 2021). Techno-economic optimization must account for these yearly environmental conditions that may influence the subsystems differently and cause interactions.…”

Experimental and Numerical Evaluation of Solar Receiver Heat Losses of a Commercial 9 MWe Linear Fresnel Power Plant

“…The experimental heat losses as well as the heat losses evaluated using the manufacturers' data are expressed in terms of heat loss divided by the length of the studied system. They refer to linear heat losses that enable direct comparisons between the different Fresnel manufacturing designs [25,27,31,32]. The experimental heat losses are obtained for different wind conditions as shown in the Figure 7.…”