Energy Forecasting Challenge
The decentralized expansion of renewable energies is an important pillar on the way to the energy transition. Self-generation systems on industrial and commercial sites are a major field of application. Primarily, customers use the electricity they generate themselves and purchase electricity if the quantities generated are insufficient. The resulting residual load (residual load = energy demand – self generated energy) must be provided by the energy supplier.
In order to ensure a stable energy supply, the energy suppliers rely on forecasts of these residual loads. In the past, those residual loads could be forecast based on many years of experience. Now, the share of solar energy systems and therefore the amount of energy self-generation increases more and more. This makes the task of forecasting the residual loads more and more complex as there are dependencies on external factors like the weather. However, the forecast is necessary to maintain a proper supply operation. For this reason, it is essential to have a forecast of the residual load that is as accurate as possible.
The Challenge
is to develop an (AI) algorithm that forecasts the residual loads. The “Energy Forecasting Challenge” is hosted by hessian.AI and AI Startup Rising in cooperation with the House of Energy and Städtische Werke AG, Kassel.
Timeline
- 15.12.2022, 10 am: The challenge kick-off ✅
- 28.12.2022, at 10 am: First Hack-Session ✅
- 13.01.2023, at 1 pm: Second Hack-Session ✅
- 31.01.2023: End of Challenge ✅
- 09.02.2023: Final Event in Kassel. Go to registration
Please note that these dates are optional in order to participate. You can also join if you can not participate everywhere or just want to work on the data.
Organizers:
