Abstract

The receiver at the optical-to-thermo-hydraulic interface of a Solar Tower plant needs careful optimization in the design stage to guarantee maximum yield during operation. Due to the highly transient behavior of a Solar Tower plant, evaluation of the receiver performance based on annual yield as a figure of merit is important. In this study, a novel method for the optimization of Solar Tower molten salt cavity receivers is introduced, which integrates optical, thermal, hydraulic and operational aspects. The receiver geometry, the hydraulic layout and the aiming strategy are optimized simultaneously. The optimization objective function is based on a validated simulation model that integrates a sky discretization approach for optical assessment and an Artificial Neural Network for fast system simulation. This approach allows to accelerate the transient annual assessment such that annual thermal yield can be used as figure of merit in the iterative optimization. For the latter, an Evolutionary Algorithm adapted to the problem has been applied, which allows for identifying optimized receiver configurations with reasonable computational effort.The methodology is demonstrated by means of a 55 MWth receiver and a given Heliostat Field in southern Spain. For this example, the evolution of receiver parameters during the course of the optimization and the break-down of different loss contributions are discussed. The optimized receiver configuration delivers more than 4% higher annual yield, as compared to the reference configuration based on static design considerations. The approach’s applicability to different systems – external receivers, other heat transfer fluids, commercial scale system sizes – is discussed.

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