Renewable energy generation directly relates to weather conditions, i.e. wind for wind energy and irradiance and cloudiness for solar energy. In a market environment where offers are to be made prior to operation, and financial consequences exist for deviations from schedule, there is a strong incentive to forecast renewable energy generation. This is based on renewable energy analytics, which is to take advantage of the wealth of data that can be used today.

Trough this module, we will look at

  • why we need to forecast and what type of forecast information may be needed
  • the origin and characterization of uncertainty in renewable energy forecasting
  • the various types of forecast products one may encounter

As additional material, please start with the video interviews with industry guests and former students, involved in various aspects of renewable energy analytics. Considering first our industry guests.

  • Jesper Thiesen (ConWx) has a long track record in renewable energy forecasting and tells us about current challenges and opportunities in the field
  • Emil Larsen (Utiligize) argues that digitization and its implications might of higher importance to the actors of the energy system than renewables and the evolution of electricity markets

The module is composed of a set of video lectures, with associated quizzes. The module introduction gives an overview of the theme and topics to be covered. The lecture slides are also made available.

Renewables in electricity markets - Interview with Jesper Thiesen (ConWx)

Renewables in electricity markets - Interview with Emil Larsen (Utiligize)

Module 7 - Module introduction

Module 7 - Forecasts, why and in what form?

Module 7 - Uncertainty origins and characterization

Module 7 - Various types of forecasting products