Large-scale wind generation simulations: Estimating missing technical parameters using Random Forest
Abstract
The rapid development of renewable energy sources drives the European power systems toward a green transition. Growing shares of wind power create the need to model the variability in wind generation. For modelling using the reanalysis approach, meteorogical data along with the technical parameters of wind power plants (WPPs) are needed. This paper focuses on the technical parameters. Specifically, missing hub height and turbine type data are estimated using the random forest (RF) algorithm. Consequently, a complete onshore WPP dataset with approximately 16000 recordings in Europe is achieved. For the validation of the developed model, wind generation time series comparison for European countries is carried out. The results indicate that especially for countries with a lot of missing technical WPP data, RF shows significant improvements compared to a baseline imputation model. The applicability of the methodology for modelling future scenarios with changing WPP installations is also shown.
Info
Conference Paper, 2019
UN SDG Classification
DK Main Research Area
Science/Technology
