Simulation of High Aspect Ratio aeroplanes and wind turbines in Python: a nonlinear aeroelastic code

AMReX-based structured wind solver

My master's dissertation on wind turbine fault prediction using machine learning

A Comprehensive Julia implementation of the Vortex Lattice Method

Dashboard designed to demonstrate the power of Machine Learning to predict failures (Remaining Useful Life (RUL)) in wind turbines. To predict the date when equipment will completely fail (RUL), XGBoost is used and achieved RMSE error is 0.033964 days, which is highly accurate.

Controllers designed to the 5MW NREL wind turbine using Simulink and Fast V8

Provides Home Assistant sensors for multiple wind turbines from the Windcentrale

Wind turbine fault detection using one class SVM

In this project, I have employed various regression techniques to estimate the Power curve of an on-shore Wind turbine. Nonlinear trees based ensemble regression methods perform best as true power curve is nonlinear. I have implemented and optimized XGBoost using GridSearchCV that yields lowest Test RMSE-6.404.

Structural Health Monitoring of Wind Turbines

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

Wind Energy : A Practical Power Analysis Approach - Open Sourced Code for the Research Paper published in IEEE.

Basic design routine for domestic wind turbine design

Wind Turbine Placement Optimization in Switzerland is a project dedicated to achieving sustainable energy goals through intelligent wind turbine placement, optimizing geographical parameters with Google OR tools. Created as a course project in Sustainable Management and Technology

TurbTroll is wind-turbine control software for small psmg-based systems driving a DC load. TurbTroll is targeted at the Arduino hardware platform.

A simple Machine Learning project for modelling all the setup of a wind turbine through several regression problems, from Engie's public dataset.