This project involves two forecasting problems.
- Hourly energy demand forecasting
- Hourly wind power plant production forecasting
iTransformer, NeuralProphet, XGBoost and LightGBM models are implemented for next 1-hour and 24-hour forecasting.
The objective is providing forecasting for test.csv datasets which comprise only data of exogenous variables for a long horizon and do not include the time series of target variables.
Tested with Python 3.9.13 environment installed with pip.
Note
The datasets train.csv and test.csv in data/electricity_demand/ and data/wind_plant/ folders are private; therefore, they haven't been uploaded.