Description
The transition to a more renewable energy system comes with the challenge of designing appropriate transmission grids. Most uniform-price electricity market rely on redispatch to cure short-time congestion when grids cannot absorb all intermittent generat
Recommended Citation
Staudt, Philipp; Traeris, Yannick; Rausch, Benjamin; and Weinhardt, Christof, "Predicting Redispatch in the German Electricity Market using Information Systems based on Machine Learning" (2018). ICIS 2018 Proceedings. 7.
https://aisel.aisnet.org/icis2018/green/Presentations/7
Predicting Redispatch in the German Electricity Market using Information Systems based on Machine Learning
The transition to a more renewable energy system comes with the challenge of designing appropriate transmission grids. Most uniform-price electricity market rely on redispatch to cure short-time congestion when grids cannot absorb all intermittent generat