Industrial Solar GmbH, a subsidiary of CISH, has been awarded € 310,000 to partake in a €3M Artificial Intelligence (AI) development project as part of an R&D consortium. The project is funded by the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection, and comes as part of an AI-development initiative by “KI-Leuchttürme für Umwelt, Klima, Natur, und Ressourcen” regional ministerium department under the title AI-AuSeSol (AI-Methoden für die autarke und selbstoptimierende solare Energieerzeugung).
The consortium for the AI project AuSeSol brings together some of Europe’s top leading research centers in AI technologies such as DLR, TUM, and Fortiss, as well as pioneers in Concentrating Solar Thermal technologies (CST) such as Industrial Solar from Germany and CSP Services from Spain.
The main goal of the project is to integrate AI-based tools in solar thermal systems for industries. As such, industrial partners such as Industrial Solar are contributing to this joint effort, to bring AI-knowledge to real-life industrial operations. Industrial Solar’s system-operators in Jordan, Japanese Tobacco International (JTI), are participating in this project with their existing Fresnel system to achieve an AI-update by the end of the project as a demonstration.
The project will start in July and is planned over a 3-year period to achieve several milestones represented by AI tools tackling design or operational inefficiencies in the CSTs. Most notably, an active weather predictive sensor, automated condition monitoring, automated operation, and predictive preventive maintenance. Deep machine learning methodologies such as convolutional neural networks (CNN), deep reinforcement learning, are utilized to employ for data compilation, image recognition, explainable anomaly detection, and feature detection. These add-ons will allow the CST systems to predict weather conditions such as cloud formations and integrate the predicted input in their control algorithms to achieve active control. Moreover, condition monitoring tools will optimize the operative aspects of the system. Additionally, the predictive preventive maintenance will decrease costs while improving the system’s overall lifetime and yield.
Upon the completion of the project, the developed AI tools will be integrated into existing operational CST systems such as the Fresnel system in Amman on JTI’s factory roof. Several PhD publications will be discussing different topics within the project’s framework. The developed AI tools will be available to be integrated in future CST installations.
The project is funded by the by the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection with a total funding volume of €3M, of which Industrial Solar will receive €310,000 with a funding rate of 50%.