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Título
Stochastic modelling of sandstorms affecting the optimal operation and cleaning scheduling of air coolers in concentrated solar power plants
Autor(es)
Palabras clave
Concentrated solar power
Air coolers
Fouling
Cleaning scheduling
Sandstorms
Clasificación UNESCO
3303 Ingeniería y Tecnología Químicas
Fecha de publicación
2020
Editor
ELSEVIER
Citación
Federico Lozano-Santamaria, José A. Luceño, Mariano Martín, Sandro Macchietto, Stochastic modelling of sandstorms affecting the optimal operation and cleaning scheduling of air coolers in concentrated solar power plants, Energy, Volume 213, 2020, 118861, ISSN 0360-5442, https://doi.org/10.1016/j.energy.2020.118861. (https://www.sciencedirect.com/science/article/pii/S036054422031968X)
Resumen
[EN]The operation performance of air-coolers in concentrated solar power plants decays due to particulate deposition on heat transfer surfaces. The deposition process can be seen as a stochastic phenomenon. A modelling approach is proposed to capture the uncertainty and the effect of extreme events, such as sandstorms, affecting the performance of plants located in dry places through dust or sand deposition on the air coolers. A case study of a concentrated solar power plant located in Dubai is analysed. Sandstorms generate acute and drastic fouling of the air coolers, and this is modelled as a stochastic process using historical aerosol dispersion data. Ten scenarios are generated by sampling the probability distribution of sandstorms occurrence and intensity. The optimal operation (cleaning schedule and airflow profiles) of the air coolers is established using Benders decomposition to solve the resulting large-scale mixed integer non-linear programming problem. The results of the stochastic scenarios demonstrate that substantial savings of $ 0.6 M − $ 2.7 M per year are achieved by the optimal operation. Cost is minimized by a combined reactive and proactive cleaning policy which accounts for the frequency, intensity and seasonal variability of sandstorms, in addition to the variability on local radiation and weather conditions.
URI
ISSN
0360-5442
DOI
10.1016/j.energy.2020.118861
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