Forecasting plays an essential role in energy economics. With new challenges and use cases in the energy system, forecasts have to meet more complex requirements, such as increasing temporal and spatial resolution of data. The concept of machine learning can meet these requirements by providing...

With an ongoing energy transition, the electric network is increasingly challenged. Handling congestion is a major responsibility of network operators. In recent years, market-based approaches to utilize network-supportive exibility, especially local exibility markets (LFMs), have been discussed...

With a growing number of distributed energy resources, the electricity network is challenged with a higher quantity of technical problems such as capacity congestions and over- or under-voltages. One often-discussed approach to solve these problems, especially in the European zonal electricity...

With an ongoing energy transition, the electric network is increasingly challenged. Handling congestion is a major responsibility of network operators. In recent years, market-based approaches to utilize network-supportive exibility, especially local exibility markets (LFMs), have been discussed...

Forecasting plays an essential role in energy economics. With new challenges and use cases in the energy system, forecasts have to meet more complex requirements, such as increasing temporal and spatial resolution of data. The concept of machine learning can meet these requirements by providing...

With a growing number of distributed energy resources, the electricity network is challenged with a higher quantity of technical problems such as capacity congestions and over- or under-voltages. One often-discussed approach to solve these problems, especially in the European zonal electricity...