Optimization of minute-scale power forecasts of offshore wind farms using long-range lidar measurements and data assimilation
The ParkCast project aims to develop, optimize and evaluate new methods for short term forecasts of the performance of offshore wind farms. The power forecasts focus on the time range up to 60 minutes with high temporal resolution.
The aim is to significantly improve the temporal resolution and forecasting quality of the parking performance in the above-mentioned time period and thus make a contribution to grid stability and supply security.
To this end, long-range lidar measurement data are assimilated into a high-resolution, local weather model using new methods based on machine learning (ML). Physical and advanced ML-based prediction models are then used for the power prediction and validated in real time for the alpha ventus offshore wind farm as part of an online test phase.