Probabilistic Intraday Forecasting of PV power generation for the Swiss Plateau

Forecasts of generated photovoltaic power tend to produce large forecast errors. The project aims to provide a framework for more accurate forecasts of solar irradiance and photovoltaic power generation over the Swiss plateau.


  • Lead school School of Engineering and Computer Science
  • Institute Institute for Data Applications and Security (IDAS)
  • Research unit IDAS / Management Science, Innovation, Sustainability and Entrepreneurship (MSIE)
  • Funding organisation SNSF
  • Duration (planned) 01.01.2022 - 31.12.2025
  • Project management Prof. Dr. Angela Meyer
  • Head of project Angela Meyer
  • Project staff Alberto Carpentieri
  • Partner ETH Eidg. Technische Hochschule
    Finnish Meteorological Institute
  • Keywords Photovoltaic, PV, intraday forecasts, photovoltaic forecasting, Radiation sensor network, Probabilistic forecasting


The installed photovoltaic power capacity is expected to grow by up to 500% in Switzerland in the next 15 years and to expand similarly strongly in other European countries. The intraday forecasts of generated photovoltaic power that are in operational use today are mostly based on weather forecast models and tend to produce large forecast errors, in particular in changeable and cloudy weather conditions and for short forecast horizons. More accurate intraday forecasts of the generated solar power and a better understanding and quantification of the forecast uncertainties are required to enable a more cost-efficient solar plant operation and reduce the cost incurred by grid operators and utilities for standby and storage capacities as well as sub-optimal bidding in the intraday and balancing markets.

Course of action

The goal of this project is to provide a framework for more accurate and reliable intraday forecasts over the Swiss plateau where most current and additional future Swiss PV capacity will be located. Specifically, the project aims to develop more accurate, probabilistic forecasting methods of the global horizontal irradiance (GHI) and the resulting generated PV power with quantified forecast uncertainties for forecast lead times of minutes to several hours.


The expected results include the provisioning and publication of the forecasting framework and its application and characterization in case studies. This project will facilitate an improved risk management and reduced operational cost through more accurate and reliable forecasts. The forecasting framework and results will be presented and provided to PV plant and grid operators in the course of the project.

The forecasts of generated PV power tend to produce large forecast errors.
The forecasts of generated PV power tend to produce large forecast errors.

This project contributes to the following SDGs

  • 7: Affordable and clean energy
  • 8: Decent work and economic growth
  • 9: Industry, innovation and infrastructure
  • 13: Climate action