pyaf/load_forecasting
Forecasting electric power load of Delhi using ARIMA, RNN, LSTM, and GRU models
This project helps electricity grid operators and energy managers predict future electricity demand. By taking historical load and weather data for Delhi, it generates daily forecasts of electricity load using various time series models. Power system engineers, grid dispatchers, and energy analysts responsible for balancing supply and demand would use this.
620 stars.
Use this if you need to accurately forecast short-term electricity demand for a specific region based on historical patterns and weather.
Not ideal if you require long-term strategic energy planning or need to forecast demand for non-electricity utilities like gas or water.
Stars
620
Forks
162
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Mar 05, 2026
Commits (30d)
0
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