Heliostat field aiming strategy based on deterministic optimization: An experimental validation

In Solar Power Tower plants, the aiming strategy plays a key role in the performance and interaction between heliostat field and receiver. This work presents an aiming strategy based on a deterministic optimization that maximizes the flux uniformity and minimizes the spillage losses. The algorithm can be fed either by a flux mapping model or by the synthesis – superposition – of experimental images. Both approaches are experimentally tested at PROTEAS research facility, aiming 16 heliostats at a flat Lambertian target. In the comparison between experimental and computed flux maps, the cross-correlation coefficient exceeds 97%. The spillage loss factors are underestimated by the computations: 9.2 percentage points by the model-based and 6.7 points by the synthesis-based approach. • Procedure to infer mirror slope errors and scale heliostat experimental images. • Aiming strategy tested at PROTEAS with 16 heliostats aiming at the water-cooled target. • The synthesis-based aiming superposes the heliostat images collected beforehand. • Uniform flux distributions decrease the peak concentration by 100 suns, compared to single-point aiming. • Spillage loss underestimated by 9.2 and 6.7 percentage points, respectively by model and synthesis-based approaches.