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At least 19 records

Commercialization of a Non-Intrusive Optical (NIO) Technology to Measure Heliostat Optical Errors in Utility-Scale Concentrating Solar Power Plants: Final TCF Report

The drone-based Non-Intrusive Optical (NIO) Technology has been developed at NREL to allow for efficient and automated optical characterization of heliostats in Concentrating Solar Power (CSP) plants. For this project, the technology will be developed into a commercial tool package, including software and user-interface (UI), operations manual, and training and support services. The project team will partner with Tietronix to perform market assessment and stakeholder engagement, develop the tool package and business model, and perform data collection and analysis to demonstrate and refine the capabilities for use at a commercial plant. The team will collaborate with a commercial plant to conduct the data collection operations and provide optical error deliverables. The goal of the project is to advance the commercialization of the technology to a stage where a beta version can be demonstrated at additional commercial plants and developed into a licensable product.

14 SOLAR ENERGY↗

Light Detecting and Ranging (LIDAR) for in-situ heliostat optical error assessment

A system and method for optical assessment of a heliostat includes obtaining a point cloud data representing an image of the heliostat; isolating the data; filtering and fitting the filtered heliostat data to a bounding box; translating the heliostat data to a plane to aid in segmentation; segmenting a plurality of facets of the heliostat fitting each of the segmented facets to a respective plane; generating normal vectors characterizing each of the plurality of facets; and calculating a canting angle associated with each respective facet of the plurality of facets. A heliostat with mirrored facets and a scanner are provided. The scanner captures point cloud data representing the heliostat, which is segmented for each facet. Normal vectors characterize the facets and a canting angle is calculated for the respective facet.

Small, Daniel E.↗

Heliostat optical error inspection with polarimetric imaging drone

On a Concentrated Solar Power (CSP) field, optical errors have significant impacts on the collection efficiency of heliostats. Fast, cost-effective, labor-efficient, and non-intrusive autonomous field inspection remains a challenge. Approaches using imaging drone, i.e., Unmanned Aerial Vehicle (UAV) system integrated with high resolution visible imaging sensors, have been developed to address these challenges; however, these approaches are often limited by insufficient imaging contrast. Here, in this study, we report a polarimetry-based method with a polarization imaging system integrated on UAV to enhance imaging contrast for in-situ detection of heliostat mirrors without interrupting field operation. We developed an optical model for skylight polarization pattern to simulate the polarization images of heliostat mirrors and obtained optimized waypoints for polarimetric imaging drone flight path to capture images with enhanced contrast. The polarimetric imaging-based method improved the success rate of edge detections in scenarios which were challenging for mirror edge detection with conventional imaging sensors. We have performed field tests to achieve significantly enhanced heliostat edge detection success rate and investigate the feasibility of integrating polarimetric imaging method with existing imaging-based heliostat inspection methods, i.e., Polarimetric Imaging Heliostat Inspection Method (PIHIM). Our preliminary field test results suggest that the PIHIM hold the promise to enable sufficient imaging contrast for real-time autonomous imaging and detection of heliostat field, thus suitable for non-interruptive fast CSP field inspection during its operation.

CSP Field↗

LiDAR For Heliostat Optical Assessment (Final Report)

This project has sought to develop new uses for surveying-quality Light Detecting and Ranging (LiDAR) 3D scanning sensors in the automatic/autonomous assessment of optical errors in largescale concentrating solar power heliostat fields. Past experiments have demonstrated the ability of a 3D-LiDAR to acquire highly accurate point cloud measurements across several Sandia NSTTF heliostats. The goal of this project is to expand upon this work to see if and how it can be used in large commercial heliostat fields.

14 SOLAR ENERGY↗

A Non-Intrusive Optical (NIO) Method to Measure Optical Errors of in-situ Heliostats in Utility-Scale Power Tower Plants: Detecting Uncertainties in Heliostat Geometry

Heliostat optical errors can account for significant losses in efficiency of power tower concentrating solar power (CSP) plants. Accurately measuring heliostat optical errors can help to improve plant performance. A Non-Intrusive Optical (NIO) method has been developed to efficiently measure heliostat optical errors from UAS collected images of the mirror surface reflection [1]–[3]. In some cases, plant data of heliostat geometry can be incomplete or contain inaccuracies, in which case field collected data can be used to detect and correct uncertainties, which is valuable information for plant operators.

Mitchell, Rebecca↗

Unmanned Aerial Vehicle Path Generation for Image Collection to Assist Heliostat Field Optical Characterization

This paper focuses on applications of unmanned aerial vehicles (UAVs) for measuring optical error of heliostats in concentrating solar power (CSP) plants. In CSP, there is a need to measure solar-field optical errors, which is critical for future production improvement as well as for operations and maintenance of a heliostat field. This latter need is particularly challenging because of the large number of heliostats (over 10,000 for a utility-scale power plant) that individually track the sun in the field. To address this issue, a camera-equipped UAV, with an optimized drone flight path developed and uploaded to it, collects images of a precise reflection of the tower on each heliostat to evaluate optical error sources without interrupting plant operation. Generation of the drone path for capturing the reflected images is affected by a number technical and realistic constraints, which include the camera angle used to capture the image, the blocking of the camera view due to surrounding heliostats, the location of the camera in reference to the target heliostat, and the target heliostat position with reference to the tower. The effect of these constraints on calculating the camera position will be discussed in detail in this article. An effective drone-path algorithm is generated to fulfil the need of image collection under various constraints.

concentrated solar power↗

Demonstration and Automation of Reflected Target Optical Measurement for Heliostats

Accurate optical surfaces are a primary driver of concentrated solar power plant performance. Errors in pointing and tracking mirrors, the canting of individual mirror facets, and the surface slope of the mirror itself can be caused by errors during assembly, transportation, wind loading, gravity, and many other sources. The tools that exist to measure these error sources today largely rely on fringe deflectometry (SOFAST, QDec, others), or photogrammetry with targets attached to the mirror surface. Since 2022, NREL has been developing a measurement method called the Reflected Target Non-intrusive Assessment (ReTNA) system. This system differs from most established methods in that we perform deflectometry with a pattern of coded targets, identified in space with photogrammetry. Reflected target systems have several advantages over traditional fringe deflectometry systems. Firstly, they can be operated in bright or ambient lighting, a challenge for fringe systems that use a projector and screen. Reflected target systems also can use a much lighter and less expensive target than projector-based systems. Lastly, 2D slope measurement can be solved from a single image, which leads to several advantages for accommodating faster measurements and smaller sized targets. These advantages make ReTNA particularly well-suited for applications where there are space or lighting constraints, like performing heliostat quality assurance on an assembly line. It's also useful when a lightweight, flexible system is needed, like for heliostat developers to quickly measure a new heliostat design at different orientations, to observe gravitational effects on the mirror surface shape. In the last year, significant improvements were made to this tool to make it more useful for these applications. These improvements were focused around validation of the ReTNA measurement system, and automation of the setup and measurement process. First, we present an improved ReTNA layout, for use on the heliostat assembly line. Next, we detail the various changes to the ReTNA software and computer vision methods to automate data collection in this new setup, and lessons learned from this process. The goal with this new setup is to perform a full heliostat surface characterization without removing the mirror from the assembly line. Lastly, we share results from several ReTNA validation studies undertaken over the last year. These include repeated ReTNA measurement on demonstration mirror facets, comparisons with other optical measurement tools, and some studies aimed at quantifying the uncertainty of ReTNA measurement under various constraints (mirror-target spacing, camera resolution, etc.). These results are compared with 2024 HelioCon performance targets, and our planned next steps for the ReTNA measurement system are presented.

CSP↗

Commercialization of Reflected Target Non-Intrusive Assessment (ReTNA) Tool, for Indoor Optical Analysis of Heliostats

Under HelioCon, NLR began developing a new optical measurement system, called Reflected Target Non-Intrusive Assessment (ReTNA). ReTNA has shown promise towards addressing metrology gaps for heliostat used in concentrated solar thermal (CST) plant. This project is focused on advancing this measurement system from the laboratory into industry, where it can provide valuable information for heliostat developers during research, development, and qualification of a heliostat design, and be used for quality assurance during heliostat manufacture. Over the course of this project, ReTNA was deployed at several commercial heliostat facilities. The system developed and deployed with the primary project partner, Solar Dynamics LLC, is described in detail. The report discusses each project Milestone, the ending status, the achieved value, and how these Milestones improve and qualify the ReTNA measurement tool. Finally, the final report covers the market advancements, path forward, commercial successes, and lessons learned. Final Technical report for TCF Base Technology-Specific project TCF-23-20118, Commercialization of Reflected Target Non-Intrusive Assessment (ReTNA) tool, for indoor optical analysis of Heliostats.

14 SOLAR ENERGY↗