Deliverable D7.3. Key features determined with machine learning

This deliverable uses the integrated simulation framework created in the UPWARDS project to reveal key features relevant for technical and social objectives. The Høg-Jæren Wind Farm in Norway is used as a case study with realistic atmospheric conditions and flow field simulations on park level. We applied data mining and machine learning techniques to train a model, which allows a study on parameters that have been fitted on simulated flow field data. This allows to extract findings on configurable dependencies in between power production and noise emission. We show that the integrated simulation framework holds huge potential to explore other scenarios and include more social and environmental factors for machine learning. We also discuss how the simulation framework can be used in various stages of wind power development. The use of this tool can be further expanded by testing for other atmospheric conditions and for different geographical contexts.