<p>The share of wind power in the generation of electricity has increased significantly in recent years and, despite its volatility, variable energy from wind turbines has become an essential pillar for the power supply in many countries around the world. To investigate the effects of increasing variable renewables on power grids, the environment or electricity markets, detailed power generation data from wind turbines with high spatial and temporal resolution are often mandatory. The lack of freely accessible feed-in time series, for example due to data protection regulations, makes it necessary to determine the wind power feed-in for a required region and period with the help of numerical simulations. Our contribution demonstrates how such a numerical simulation can be developed using publicly available wind turbine and weather data. Herein, a novel model approach will be presented for the wind-to-power conversion, which utilizes a sixth-order polynomial for the specific power curve of a wind turbine. After such an analytical representation is derived for a certain turbine, its output power can be easily calculated using the wind speed and air temperature at its hub height. For proof of concept and model validation, measured feed-in time-series of a geographically and technically known wind turbine are compared with the simulated time-series at a high temporal resolution of 10 minutes. In order to determine the power generation for larger regions or an entire country the derived numerical simulation is also carried out for an ensemble of almost 26 thousand onshore wind turbines in Germany with a total capacity of about 44 GW. With this ensemble, first simulation results with municipal and hourly resolution can be presented for an annual period.</p>
Penetration of Electric Vehicles toward 2050: Analysis Utilizing an Energy System Model Incorporating High-Temporal-Resolution Power Generation Sector
