Advanced Controllers for Heat Transfer Fluid Mass Flow Rate Control in Solar Tower Receivers

Cody B. Anderson; Giancarlo Gentile; Alessandro Longhi; Francesco Casella; Michael E. Cholette; Giampaolo Manzolini

doi:10.52825/solarpaces.v2i.913

Authors

Cody B. Anderson Queensland University of Technology https://orcid.org/0000-0002-0153-3883
Giancarlo Gentile Politecnico di Milano https://orcid.org/0000-0002-1504-4298
Alessandro Longhi Politecnico di Milano https://orcid.org/0009-0008-5137-1801
Francesco Casella Politecnico di Milano https://orcid.org/0000-0002-4509-0711
Michael E. Cholette Queensland University of Technology https://orcid.org/0000-0003-2649-3942
Giampaolo Manzolini Politecnico di Milano https://orcid.org/0000-0001-6271-6942

DOI:

https://doi.org/10.52825/solarpaces.v2i.913

Keywords:

Control Systems, Concentrated Solar Thermal, Modelica, Lifetime Prediction

Abstract

Efficient control strategies for managing the mass flow rate (MFR) of heat transfer fluids (HTF) during cloud transients in Solar Tower receivers play a pivotal role in optimizing plant profitability and receiver durability. This study focuses on the performance and durability of Solar Tower receivers during cloud transients. It evaluates adaptive feedback and feedforward control methods, which adjust the flow rate of heat transfer fluids based on real-time measurements of direct normal irradiance (DNI), receiver outlet and receiver panel outlet temperatures. The effectiveness of an aggressive all-sky and conservative clear-sky control strategy is explored against a conventional PI controller, emphasizing energy efficiency and receiver longevity. Simulations using a thermal Modelica model resembling a 100 MW_el Crescent Dunes-like solar tower plant reveal that both advanced controllers provide precise setpoint tracking, while the PI controller struggles. The conservative controller which has a cloud standby mode prevents overheating during cloud transients by using a clear sky mass flow rate, while the aggressive controller uses the receiver panel outlet temperatures to correct for upstream tube temperature variations allowing for fast tracking correction and disturbance rejection, albeit with slight overshoots. Furthermore, the controllers significantly decrease the creep-fatigue damage accumulated in the receiver panels during cloudy days, due to limiting the increase in wall temperature spikes when cloud events end. Overall, this study underscores the pivotal role of HTF mass flow rate control systems in influencing receiver system failure modes and longevity and offers a new tool in controller design and operation assessment.

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References

R. W. Bradshaw et al., “Final Test and Evaluation Results from the Solar Two Project,” Contract, no. January, p. 294, 2002, doi: https://doi.org/10.2172/793226.

B. Nouri et al., “Optimization of parabolic trough power plant operations in variable irradiance conditions using all sky imagers,” Solar Energy, vol. 198, no. December 2019, pp. 434–453, 2020, doi: https://doi.org/10.1016/j.solener.2020.01.045.

S. Kannaiyan and N. D. Bokde, “Performance of Parabolic Trough Collector with Different Heat Transfer Fluids and Control Operation,” Energies (Basel), vol. 15, no. 20, Oct. 2022, doi: https://doi.org/10.3390/en15207572.

G. Gentile, G. Picotti, M. Binotti, M. E. Cholette, and G. Manzolini, “Dynamic thermal analysis and creep-fatigue lifetime assessment of solar tower external receivers,” Solar Energy, vol. 247, no. May, pp. 408–431, 2022, doi: https://doi.org/10.1016/j.solener.2022.10.010.

G. Gentile, G. Picotti, F. Casella, M. Binotti, M. E. Cholette, and G. Manzolini, “SolarReceiver2D: a Modelica Package for Dynamic Thermal Modelling of Central Receiver Systems,” IFAC-PapersOnLine, vol. 55, no. 20, pp. 259–264, 2022, doi: https://doi.org/10.1016/j.ifacol.2022.09.105.

M. J. Wagner and T. Wendelin, “SolarPILOT: A power tower solar field layout and characterization tool,” Solar Energy, vol. 171, no. June, pp. 185–196, 2018, doi: https://doi.org/10.1016/j.solener.2018.06.063.

W. T. Hamilton, M. J. Wagner, and A. J. Zolan, “Demonstrating SOLARPILOT’s Python Application Programmable Interface Through Heliostat Optimal Aimpoint Strategy Use Case,” Journal of Solar Energy Engineering, Transactions of the ASME, vol. 144, no. 3, pp. 1–7, 2022, doi: https://doi.org/10.1115/1.4053973.

C. Maffezzoni, G. A. Magnani, and S. Quatela, “Process and Control Design of High-Temperature Solar Receivers: An Integrated Approach,” IEEE Trans Automat Contr, vol. AC-30, no. 3, pp. 194–209, 1985.