DBU_HELIOS - Predictive Spatial Analytics for Solar Energy Grid Integration: Enhancing Reliability and Efficiency

Project background

Solar power forecasts play an important role in accelerating and promoting the transition to sustainable energy production energy generation, distribution and use. Reliable forecasts contribute to help to plan and optimize the use of solar energy more effectively. This will increase the share of renewable energy in the overall energy mix and reduce the ecological footprint of energy generation. This is an important step towards an environmentally friendly and sustainable energy energy infrastructure.

Project objective

The aim of the "Helios" project is to develop temporally and spatially high-resolution short-term forecasts for solar radiation. By analyzing all-sky images, cloud objects and classes are identified in order to and classes of clouds are identified to gain more detailed insights into irradiance excesses and volatilities. The analysis improves the understanding of the interplay between solar irradiance and cloud movements.

One focus is on the on the connection of solar radiation forecasts with real energy yields from a PV research field (digital twin). The further development of meteorological parameters enables a deeper understanding of the areal distribution of solar radiation. Particular attention is paid to the influence of the influence of cloud types and edges on the areal solar radiation distribution in order to develop advanced camera-based solar power forecasts.

Project procedure

Together with our project partners, at the start of the project we take extensive meteorological measurement technology (including cloud cameras, pyranometers, ceilometers) on a PV research field. Thanks to the data already data already available from a preliminary study, we can start developing algorithms and algorithms and methods for cloud detection in all-sky images. at the same time. We will then concentrate on cloud classification and tracking. The algorithms developed will be gradually applied to the PV research field and continuously optimized.

Based on the previous results previous results, a PV forecast is then developed. The collaboration with our cooperation partners ensures an interdisciplinary interdisciplinary processing of the research project.

Innovation

Our solar radiation forecast will be integrated into the Digital Twin of the PV research field. This integration opens up the possibility of precisely linking the solar radiation forecasts with the real-time monitoring data from the VCOM Cloud from meteocontrol GmbH and continuously optimizing them. A key aspect is the improvement in the areal resolution of the solar radiation, which enables finer control of the system, which in turn leads to optimized energy generation. Our comprehensive measurement technology also enables a holistic view and analysis of the ambient conditions.

The data collected, combined with the photovoltaic yields achieved and the derived solar radiation values, form the basis for a pioneering AI-based method for precise cloud classification. These innovation approaches strengthen the accuracy and efficiency of solar radiation forecasts and help to further optimize the integration of fluctuating energy producers.