Research Project HyForPV

Hybrid solar radiation forecasts and scalable calculation methods for system integration and marketing of PV electricity

A new forecasting method based on a combination of different data sources is being developed and standardised in the HyForPV research project for the purposes of system integration and further expansion of photovoltaics. The energy supplied from photovoltaic systems depends heavily on the weather and can fluctuate by the minute or even second. Grid operators face the challenge of integrating this fluctuating energy source into the likewise highly volatile balance between electricity supply and demand. For system integration and the further expansion of photovoltaics there is therefore a great need to develop and standardise new products that enable forecasts.

Research project HyForPV

 

Duration

September 2018 until August 2021

Funded by

Federal Ministry for Economic Affairs and Energy (BMWi)

Project participants

  • Institute of Networked Energy Systems
  • Bundeshöchstleistungsrechenzentrum Stuttgart
  • capdevila ite e.K., Stuttgart

The HyForPV research project is developing a forecasting method that can combine data sources with different resolutions (satellite images, weather models, simulations, cloud cameras) with the aim of developing high-resolution PV power forecasts. Optimised data processing on high-performance computers is used to create short-term forecasts that are characterised by a high update rate of around five minutes and a forecast horizon of one hour. The forecasting method should also allow individual forecasts to be scaled to area-based forecasts for all installed systems, for example to cover entire grid areas.

The Institute of Networked Energy Systems is working on using and combining different experimental and model-based data sources such as cloud cameras, satellite data and numerical weather models as part of the project. In conjunction with the results of the eye2sky research project, which deal with the development and evaluation of cloud cameras, valuable forecasts can be made for grid and system operators. They can then use these forecasts for energy trading and the supply and storage management of solar energy.

Contact

Energy Meteorology

Research Group
Institute of Networked Energy Systems