HelioSoil: A Python Library for Heliostat Soiling Analysis and Cleaning Optimization





Soiling, CSP, Reflectance, Cleaning, Heliostats, Python, Open-Source


Soiling losses and their mitigation via cleaning operations represent important challenges for Solar Tower (ST) plants. Yet soiling losses are not well considered in existing CSP software, likely due to the lack of tools for soiling estimation and cleaning optimization. In this paper, a Python-based heliostat soiling library, called HelioSoil, is introduced which allows for the assessment of heliostats’ soiling state and the optimization of the solar field cleaning schedule to maximize plant profit. The library is freely available on GitHub under a LGPL license, which enables extensions via other Python APIs (e.g. CoPylot) and integration with other CSP plant simulation packages to consider soiling losses. This latter capability is demonstrated in this study through an LCOE assessment and cleaning optimization of a hypothetical Australian ST plant with SolarTherm. Hence, HelioSoil provides the CSP community with a package for soiling assessment and cleaning resource optimization, which can be integrated with available software for high-level, long-term simulations. HelioSoil facilitates the inclusion of soiling and cleaning costs in CSP economics and ultimately aim to de-risk the deployment of ST plants.


Download data is not yet available.


M., Blair, N., Diorio, N., Freeman, J., Gilman, P., Janzou, S., Neises, T., Wagner, M., 2018. System Advisor Model ( SAM ) General Description System Advisor Model.

F. Holmgren, W., W. Hansen, C., A. Mikofski, M., 2018. Pvlib Python: a Python Package for Modeling Solar Energy Systems. J. Open Source Softw. 3, 884. https://doi.org/10.21105/joss.00884

Picotti, G., Moretti, L., Cholette, M.E., Binotti, M., Simonetti, R., Martelli, E., Steinberg, T., Manzolini, G., 2020. Optimization of cleaning strategies for heliostat fields in solar tower plants. Sol. Energy 204, 501–514.https://doi.org/10.1016/j.solener.2020.04.032.

Truong-Ba, H., Cholette, M.E., Picotti, G., Steinberg, T.A., Manzolini, G., 2020. Sectorial reflectance-based cleaning policy of heliostats for Solar Tower power plants. Renew. Energy 166, 176–189. https://doi.org/10.1016/j.renene.2020.11.129

Wales, J.G., Zolan, A.J., Newman, A.M., Wagner, M.J., 2021. Optimizing vehicle fleet and assignment for concentrating solar power plant heliostat washing. IISE Trans. 0, 1–13. https://doi.org/10.1080/24725854.2021.1966858.

Wolfertstetter, F., Wilbert, S., Dersch, J., Dieckmann, S., Pitz-Paal, R., Ghennioui, A., 2018. Integration of Soiling-Rate Measurements and Cleaning Strategies in Yield Analysis of Parabolic Trough Plants. J. Sol. Energy Eng. 140. https://doi.org/10.1115/1.4039631

Picotti, G., Binotti, M., Cholette, M.E., Borghesani, P., Manzolini, G., Steinberg, T., 2019. Modelling the soiling of heliostats: Assessment of the optical efficiency and impact of cleaning operations. AIP Conf. Proc. 2126. https://doi.org/10.1063/1.5117555.

Picotti, G., Borghesani, P., Manzolini, G., Cholette, M.E., Wang, R., 2018. Development and Experimental Validation of a Physical Model for the Soiling of Mirrors for CSP Industry Applications. Sol. Energy 173, 1287–1305. https://doi.org/10.1016/j.solener.2018.08.066.

Seinfield, J.H., Spyros, P.N., 2016. Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, 3rd ed. John Wiley & Sons, Ltd. https://doi.org/10.1080/00139157.1999.10544295.

Hamilton, W.T., Wagner, M.J., Zolan, A.J., 2021. Demonstrating SolarPILOT’s python API through heliostat optimal aimpoint strategy use case. Proc. ASME 2021 15th Int. Conf. Energy Sustain. ES 2021. https://doi.org/10.1115/ES2021-60502.

Zolan, A., Mehos, M., 2020. Wash Vehicle Fleet Sizing for Contingency Planning Against Dust Storms. Sol. Paces 2020. https://doi.org/10.1063/5.0085675.

Scott, P., Alonso, A.D.L.C., Hinkley, J.T., Pye, J., 2017. SolarTherm: A flexible Modelica-based simulator for CSP systems. AIP Conf. Proc. 1850. https://doi.org/10.1063/1.4984560




How to Cite

Picotti, G., Cholette, M. E., Wang, Y., Anderson, C. B., Steinberg, T. A., Pye, J., & Manzolini, G. (2024). HelioSoil: A Python Library for Heliostat Soiling Analysis and Cleaning Optimization. SolarPACES Conference Proceedings, 1. https://doi.org/10.52825/solarpaces.v1i.719

Conference Proceedings Volume


Operations, Maintenance, and Component Reliability

Funding data