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Solar fields of parabolic troughs are extensive complex thermal hydraulic facilities. Intra-hour and intra-minute variabilities of the DNI, mainly caused by passing clouds, pose an operational challenge for parabolic trough power plants. Under perfect circumstances a solar field controller would adjusts the mass flow in such a way, that the design temperature is always maintained constant with a maximized focus rate. However, heterogeneous irradiance conditions or flow distribution may cause some solar field sections to temporarily overheat while others may not reach the set point temperature, which in turn leads to an economic loss. State of the art solar field controllers have only access to incomplete information on spatial DNI variability, from DNI measurements of few pyrheliometers. Solar field controllers could be optimized with access to highly resolved DNI informations both in space and time. Such DNI information can be provided by all sky imager (ASI) based irradiance monitoring systems. In a previous study we developed and benchmarked new solar field controllers with access to spatial DNI information from an ASI system for a 50 MWe plant close to Córdoba (Spain). Significant improvements in revenue were observed. Yet, this previous study was limited to 22 days only. In this study, we estimate the potential benefit of these new solar field controllers over a 2 year period on the basis of the simulation results over 22 days. The upscaling method makes use of DNI variability classes. Using the ASI data we obtain a significant improvement in revenue up to 2% for the 2 year period.

A way to increase parabolic trough plant yield by roughly 2% using all sky imager derived DNI maps