  In this work, a digital twin with standalone, descriptive, and predictive
capabilities is created for an existing onshore wind farm located in complex
terrain. A standalone digital twin is implemented with a
virtual-reality-enabled 3D interface using openly available data on the
turbines and their environment. Real SCADA data from the wind farm are used to
elevate the digital twin to the descriptive level. The data are complemented
with weather forecasts from a microscale model nested into Scandinavian
meteorological forecasts, and wind resources are visualized inside the
human-machine interface. Finally, the weather data are used to infer
predictions on the hourly power production of each turbine and the whole wind
farm with a 61 hours forecasting horizon. The digital twin provides a data
platform and interface for power predictions with a visual explanation of the
prediction, and it serves as a basis for future work on digital twins.
