Solar Tower power plants face significant challenges to ensure their worldwide deployment, including heliostat soiling leading to optical efficiency degradation and increased operation and maintenance costs due to cleaning opera- tions. Additionally, optimizing the thermal power output of the receiver is crucial and depends on the selected aiming strategy, directly affecting receiver thermal efficiency and operational lifetime.
To tackle these issues, this research proposes a methodology for the preliminary design of Solar Tower power plants’ solar fields. This methodology integrates a physical model to simulate soiling losses and optimizes cleaning schedules using a fixed-frequency time-based heuristic method. After selecting the desired aiming strategy, SolarPILOT is utilized alongside a heuristic defocusing and re-focusing strategy to simulate plant performance. Moreover, drivers failure analysis is con- sidered for improved accuracy.
Applied to Solar Tower facilities in Mount Isa, Queensland, Australia, the method- ology analyzes various solar field sizes to identify the configuration with the lowest Levelized Cost of Electricity. Results show that oversizing the solar field by five times and coupling it with a 6.5-hours Thermal Energy Storage system is optimal for turbine full-load operation, while oversizing by four times and coupling with an 11.5-hours storage system is optimal for load-based operation. A sensitivity analysis on heliostat pricing reveals a drop in field oversizing by one size when the price doubles, regardless of dispatching strategies and field cleaning conditions.
In conclusion, this research contributes to the development of a comprehensive sizing methodology for Solar Tower power plants, integrating soiling and aiming strategies and highlighting the impact of heliostat pricing and dispatching strate- gies on plant performance and economics.