Transmission grid stabilization using virtual power plants

In Germany, the ongoing expansion of decentral renewable energy sources (RES) is decreasing the full load hours of traditional power plants and consequently their profitability. In the medium and long-term this could result in a crowding out of conventional, regionally concentrated power plants. This poses increasing substantial challenges to a reliable operation of power systems. Due to the ambitious targets of the Federal Government's energy concept, the energy transition has proceeded far in Germany. Advances in information and communications technology (ICT) allow to agregate and to market distributed RES by forming virtual power plants (VPPs). In this paper, we study a grid load data set providing circuit level load time series. Based on the data set, we develop a direct current load ñow (DCLF) model of a control area region of the German transmission grid. To approximate real world congestion incidents, we develop a regressive nodal load model with the ability to reproduce the measured data. Consequentially, we study how flexibility of production of biomass powered plants aggregated to VPPs can be utilized to relax stress on the transmission grid. We show that biomass power plants can contribute to reduce grid load significantly.