Fraunhofer ISE covers a wide range of digitalization solutions in today’s and tomorrow’s PV systems, including
Efficient and reliable detection of malfunctions and energy losses is essential for reducing costs and guaranteeing successful operation. By promptly identifying issues, timely corrective actions can be taken to minimize downtime and maintain optimal performance. This proactive approach helps to extend the lifespan of the PV system, maximize energy production, and ultimately increase return on investment for solar energy projects.
Fraunhofer ISE monitoring system is particularly suited for highly innovative PV projects and technologies: Floating PV, Agri-PV, infrastructure-PV, novel PV technologies (i.e. new PV module technologies, innovative PV systems design, etc.)
Our services comprise:
Automated fault detection offers a dependable solution for identifying failures and energy losses in PV systems. By continuously monitoring system performance and utilizing advanced algorithms, it can quickly detect anomalies and pinpoint the source of issues. This proactive approach allows for swift corrective action, reducing downtime and ensuring optimal system operation.
For this purpose, multiple methods have been created to:
These techniques have been thoroughly validated using a portfolio of more than a hundred commercial PV systems.
Within the PV O&M context, the development of AI and deep-learning based algorithms is a groundbreaking approach to enhance performance and efficiency. Fraunhofer ISE offers customized algorithm development as part of research projects tailored to clients' needs. These advanced algorithms analyze vast amounts of PV system data to identify patterns and trends, optimizing system performance and automating decision-making processes. By continually adapting and evolving, AI and deep-learning algorithms play a vital role in advancing solar energy operations and management.
Fraunhofer ISE can assess the client’s own algorithms by contrasting their results with those of other algorithms tackling the same problem
Soiling detection in PV systems is crucial to optimize energy output, prevent losses, and extend lifespan.
Using a variety of algorithms (either state-of-the-art from research or Fraunhofer ISE custom developments), experts examine the results to guarantee accuracy and trustworthiness. If necessary, the process includes obtaining and analyzing meteorological data or satellite images.
Our soiling measurement service includes designing a tailored measurement concept, selecting the appropriate sensors, and conducting thorough results analysis. This comprehensive approach ensures the most effective solution for project specific needs.
IEC 61724-1:2021compliant
Fraunhofer ISE edited an IEA PVPS report on the topic: Soiling Losses – Impact on the Performance of Photovoltaic Power Plants - IEA-PVPS
The digital twin is based on Fraunhofer’s ZenitTM platform. This Python-based electrical PV simulation tool has been used on a day-to-day basis to provide scientific quality bankability analyses for project developers, investors, EPCs, and many different industrial partners along the solar power value chain. Furthermore, it is regularly developed and validated in research projects, showing a high degree of flexibility in terms of the types of solar power plants capable of being accurately simulated.
The aim of the digital twinning methodology is to provide a baseline performance calculation to help identify deviations from expected behaviour. Utilizing this information, unusual reductions in output power that might be linked to unexpected component faults or degradation can inform maintenance measures such as cleaning or repair. Furthermore, the twin’s forecasting module provides predicted yield for a coming 3-day period based on locally available weather forecasts.
At Fraunhofer ISE, we are working on the development of forecasting models for the reliable prediction of the solar power for time scales from a few minutes up to several days and areas from single locations to regions of many kilometers. For this, our team of physicists, meteorologists and IT specialists combines input data from various sources (cloud camera images, satellite-based data, numerical forecasts) into a variety of different forecast models.
Our services comprise:
Fraunhofer Institute for Solar Energy Systems ISE
