A non-intrusive optical (NIO) approach to characterize heliostats in utility-scale power tower plants: Sensitivity study. (1st September 2020)

• Record Type: Journal Article
• Authors: Mitchell, Rebecca A.; Zhu, Guangdong
• Is Part Of: Solar energy. Volume 207(2020)
• Page Start: 450
• Page End: 457
• Publication Date: 2020-09-01
• Subjects: Solar energy -- Periodicals; Solar engines -- Periodicals; 621.47
• DOI: 10.1016/j.solener.2020.06.093
• Languages: English
• ISSNs: 0038-092X

Abstract

Highlights: Develop the first-of-the-kind non-intrusive optical (NIO) characterization approach on heliostats. Provide guidelines to configure and implement the NIO tool to achieve target measurement accuracy. Characterize the impact of various design parameters to the NIO measurement uncertainty. Abstract: Power towers, a type of concentrating power tower technology, use a large number of heliostats to concentrate sunlight and produce renewable energy. Optical errors of heliostats can cause drastic losses in the efficiency of power-tower plants. Accurately measuring optical errors is crucial to assessing and improving plant performance. This analysis discusses an innovate non-intrusive optical (NIO) approach to measure slope, canting, and tracking errors by detecting distortions in the reflected tower structure in heliostat images. A sensitivity study is carefully conducted to determine the uncertainty requirements to allow the method to calculate slope errors with an accuracy of 0.25 mrad. Measurement uncertainty sources include camera resolution and position uncertainty, tower position uncertainty, and number of collected images. Each uncertainty source is investigated to determine its impact on the accuracy of the slope-error calculation. A combination of theoretical results and experimental results obtained from data collected on a heliostat at Sandia National Laboratories is used to determine and validate uncertainty requirements. The analysis shows that a measurement uncertainty of 0.25 mrad can be realized by realistically controlling uncertainty sources when implementing the NIO method. It demonstrates the superior performance of NIO in performing in-situ optical characterization.