Interaction between atmospheric model resolution and energy system model topology

With the increasing penetration of renewable energy capacities in the European energy system, the electricity generators have shifted from centralized power plants to decentralized, weather-dependent wind turbines and photovoltaic systems. Energy system models now rely on skillful weather data to estimate renewable energy feedins on electricity bus levels. These feedins are usually calculated by bilinearly interpolating the closest atmospheric model grid points to the electricity network bus locations. This comes to the cost of averaging multiple atmospheric model grid points reducing overall atmospheric model variability. In addition, electricity grids are often modeled in clustered representations in terms of number of lines and buses. The number of buses is usually much smaller than the number of atmospheric model grid points and therefore some grid points and their characteristics may not be taken into account in highly clustered networks. So far, this interconnection between atmospheric model resolution and electricity grid topology has not been widely investigated.

This study approaches the question if and to what extent the atmospheric model resolution affects the energy system model results. The regional reanalysis COSMO-REA6 is used as a reference data and its resolution is artificially reduced. This allows to compare the loss of information (mainly variability) due to a lower grid point resolution. The weather data is then used within different energy system network topologies to determine the corresponding renewable energy feedins at bus levels. A subsequent optimal power flow model estimates the impact on energy system metrics as storage usage and economic dispatch costs to further understand the relationship between atmospheric model resolution and energy system model topology. This study provides useful insights to choose the appropriate resolution of the atmospheric model input given an energy system model.