Integrating Energy Meteorology into Grid Operations

The transformation of the German energy system toward high shares of renewable energy sources introduces significant weather dependencies in power generation, consumption, and capacity of overhead lines. This presentation explores how energy meteorological information systems address these challenges in modern grid operations.
We present two key application areas: First, forecasting systems for energy systems that support redispatch planning and congestion management. Current challenges include distinguishing between "possible" and "actual" feed-in using customized AI models, as well as evaluating forecast uncertainties through probabilistic grid calculations based on ensemble weather forecasts. With probabilistic security analyses becoming mandatory for transmission system operators from 2027 onward, these methods gain critical importance. Additionally, we discuss seasonal wind energy forecasts using the German Climate Forecasting System with subsampling techniques based on circulation indices.
Second, we address weather-dependent operation of overhead lines through Dynamic Line Rating (DLR). While static assumptions based on conservative weather conditions waste transmission potential, DLR enables increased power flow by accounting for actual cooling effects. Key challenges include the accurate representation of local wind speeds along transmission corridors and managing uncertainty for non-instrumented spans.
We conclude that energy meteorological tools are essential for the safe operation and planning of energy systems with high renewable shares, emphasizing the need for ongoing collaboration between meteorology and energy systems research.