Makani was a project to develop a commercial-scale airborne wind turbine, culminating in a flight test of the Makani M600 off the coast of Norway. All Makani software has now been open-sourced. This repository contains the working Makani flight simulator, controller (autopilot), visualizer, and command center flight monitoring tools. Additionall…

Main repository for the NREL-supported OpenFAST whole-turbine and FAST.Farm wind farm simulation codes.

A curated list of open wind turbine data sets and corresponding code

python scripts for wind turbine data cleaning

Repository containing OpenAFPM wind turbine CAD model.

Wind Power Prediction with ECMWF Data as Input using Statistical Learning

A Open-Source Horizontal axis-Aero-Wave-Turbulence Coupling(HawtC) Tool for dynamic simulation of floating offshore wind turbine(FOWT).And supports the dynamic coupling simulation of the tuned mass damper and tuned mass inertia damper for wind turbine blades and towers

Data portal for NREL's Renewable Energy Potential Model.

This repository is dedicated to wind turbines power curve modeling, from data cleansing to the actual power curve modeling with various approches.

PCC-driven P²Z collector system aggregation for disaggregated plants in PSS/E (wind, solar, BESS, hybrid)

Probabilistic Wind Power Forecasting with R

The potential for repowering US wind turbines

Comparative analysis of LSTM, XGBoost, Random Forest, SVR, and SARIMAX for wind power prediction using real-world turbine data. Covers preprocessing, time series modeling, and performance benchmarking.

German wind energy forecasting framework using Python and XGBoost. Features an advanced Wide-to-Long pipeline and chronological validation. Minimizes prediction errors by 37 MW, preventing costly over-generation and optimizing reserve-capacity allocation to ensure grid stability and maximize clean energy revenue.

A 3D-printed car project for Young Engineers, demonstrating how wind energy converts into mechanical motion. Features a modular printed body, letting students experiment with different wheel sizes and sail designs to boost performance.

Code for reproducing results of extended vertical wind profile–based farm-scale power forecasting study.

Interactive maps of new windmills in Bayern and Germany

XGBoost-based wind power forecasting with multi-height meteorological data

Random Forest model to predict wind power generation output. Features: data preprocessing, feature engineering, model training, evaluation metrics, and visualization. Built with scikit-learn and pandas.

Deep learning project for short-term wind power forecasting using LSTM and Random Forest