Welcome to NWDBT3

This is the Github repository for National Wind Database Task 3! T3 uses machine learning algorithms to provide stochastic power curve modeling.

Installing packages

NOTE: The installation instruction below assume that you have python installed on your machine and are using conda as your package/environment manager.

1. Create a new environment: conda create --name nwdbt3 python=3.8
2. Activate environment: conda activate nwdbt3
3. Install packages listed in rq.txt

Code scipts

1. manupc_cleaning.py cleans the raw data in Data/All/.
   Example of data cleaning.
   
2. ANN_trainging.ipynb trains the model for a single turbine.
   Example of wind turbine uncertainty modeling.
   
3. ProbMetrics_2.R calcualates the metrics for wind turbine uncertainty quantification.
4. Analysis_SPC_WindRegion.R outputs the relialibility and sharpness plots.
   

  Example of reliability plot.          Example of sharpness plot.

Example of time series plot.

Recommended Citation

Please check back in the future

Acknowledgments

Funding provided by the DOE Wind Energy Technologies Office (WETO).