Tietronix
Digital Twin and Industry 4.0 in support of Heliostat Technology Advancement
Principal Investigator: J. Roger Angel angelj@email.arizona.edu
DOE ID: 38488-006
Project Title: Digital Twin and Industry 4.0 in Support of Heliostat Technology Advancement
PI: Michel Izygon, Tietronix
NREL TM: Shashank Yellapantula
Sandia POC: Jeremy Sment
POP: 04/04/23–10/31/24
Budget: $499,972
Abstract: The project’s main objective was to apply multiple technologies from Industry 4.0 to heliostat design, manufacturing, deployment, and operations in order to realize the cost reduction seen by other industries that have adopted these technologies. Industry 4.0 technologies such as model-based system engineering (MBSE), virtual and augmented reality, machine learning, industrial internet of things (IIoT), and digital twins are transforming the manufacturing sector as well as the entire life cycle of complex physical systems. By adopting these technologies during the design, manufacturing, and operations phases of the heliostat field, future CSP plants will benefit from the same cost reductions, performance increases, lowered risks, and improved reliability that the automotive and aerospace industries have realized in the past few years.
Actual Outcome: The project team from Tietronix applied the MBSE approach to develop a full set of systems modeling language (SysML) models that capture the heliostats’ solar field requirements, overall architecture and detailed component design, interactions between components, behavior and failure modes, and the key equations that define the heliostats’ operations. The SysML models can be used by the solar thermal industry as a template to facilitate their adoption of the MBSE methodology.
The team also developed multiple instances of digital twins for a single heliostat and for entire solar fields, and demonstrated how these digital twins can support various use cases, such as visualization, simulation, and performance optimization. The team demonstrated an instance of a digital twin of a heliostat manufacturing facility to prove the possibility of optimizing the assembly line before it is built in order to minimize the rework and associated cost increase. Additionally, Tietronix team showed how virtual and augmented reality can be used to improve the layout of the assembly line or train technicians on heliostat maintenance.
Impact: Digital twins of solar fields can lead to increased solar field performance, improved heliostat asset lifespan, and overall enhanced operational efficiency. This is achieved by optimizing operations, reducing downtime, improving maintenance scheduling, and enabling proactive decision-making based on real-time data insights. The solar field digital twin developed in this work has been proven to support a large set of use cases for the solar field industry, from optimization of manufacturing automation to better insights into design decisions to early visualization of the proposed concept, operational issues, and anomalies. By understanding potential performance challenges early in the life cycle, solar field operators can significantly improve performance.
Figure 11. Digital twin of one heliostat at the NSTTF, playing back the log file of an experiment operation. The digital twin provides visualization of the heliostat motion and displays the telemetry data captured during the experiment.
Figure 12. Digital twin of one heliostat at the NSTTF, playing back the log file of an experiment operation. The digital twin provides visualization of the heliostat motion and displays the telemetry data captured during the experiment.