Renewable Energy Forecasting Summer School, Rio de Janeiro, October 2020 – virtual

Henrik Madsen, center director of CITIES and professor at DTU Compute, is invited to Rio de Janeiro in Brazil in October 2020 to hold: Renewable Energy Forecasting Summer School.

Following upon the global measures to contain and mitigate the spread of COVID-19, the IIF Board of Directors has postponed this event from July to October.

The IIF Summer School is a two-day course which provides in-depth analysis of a cutting edge topic in forecasting from one of the International Symposium on Forecasting (ISF) invited speakers. The Summer School typically shares the same venue as the ISF.

Renewable Energy Forecasting – Theory and Practice

Today, on average, roughly 50 per cent of the electricity in Denmark is generated as wind and solar power. Wind power alone accounts for around 44 per cent of the electricity load, but this is highly fluctuating. Denmark has hours with almost no wind but also experiences periods with up to 140 per cent of the electricity load. Therefore, forecasting is crucial in order to operate the energy systems including the electricity grid. Prof. Madsen and his collaborators are responsible for the methods used, eg. in Denmark, by both transmission system operators and low voltage operators.

Through a combination of lectures and lab sessions, this course will provide an introduction to methods and tools used for forecasting wind and solar power generation. We will touch upon how the forecasts are used in the daily operation of the power system. For the lab session, R software packages will be used. The topics covered are:

  • Point forecasts and probabilistic forecasts
  • Use of meteorological (MET) forecasts
  • Simple parametric models for forecasting (Box-Jenkins, SARIMA, Holt-Winter, Neural Networks, AI, Hidden Markov, Regime based models)
  • Non- and Semi-parametric methods (Kernel, Spline, Local polynomial, and Varying coefficient based methods)
  • State spaces models in discrete and continuous time
  • Multivariate probabilistic forecasting
  • Methods for forecast evaluation
  • Spatio-temporal forecasting
  • Forecasting hierarchies
  • Combined forecasting (eg. for use of several MET providers)
  • Down- and upscaling
  • Adaptive forecasting
  • Generating forecasts for optimal decision making
  • Tools for wind and solar power forecasting

The course will also provide options for the best tool depending on the penetration level of the renewables and the setting in general.

Interested in attending Henrik Madsen’s summer school? Read more about the course in Rio here.

The power lines meander in the favela Vidigal on a hillside in Rio de Janeiro. Photo: Hanne Kokkegård