Stochastic modelling of sandstorms affecting the optimal operation and cleaning scheduling of air coolers in concentrated solar power plants

Abstract

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.