This repository contains algorithms, datasets, and models for analyzing and optimizing wind turbine power curves to enhance energy efficiency in renewable energy systems.
- Algorithms: Includes implementations of algorithms such as XGBoost for analyzing power curve data.
- Datasets: Provides datasets used for training and validating power curve models.
- Models: Contains machine learning models developed for predicting and optimizing wind turbine performance.
- Contributing: Guidelines for contributing to this repository. We welcome contributions such as bug fixes, enhancements, and new algorithms/models.
XGBRegressor from the XGBoost library is used for predicting wind turbine power output based on various input features. Below is a brief guide on how to use XGBRegressor for power curve analysis.
First, make sure you have the necessary libraries installed. You can install them using pip:
pip install xgboost