The repository consists of an energy forecasting model using XGboost. The dataset consists of hourly energy consumption rates in kWh for an industrial utility.
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Updated
May 1, 2023 - Jupyter Notebook
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energy-forecasting-model
Here are 3 public repositories matching this topic...
Dockerized FastAPI service for forecasting Germany’s hourly electricity load using real Open Power System Data (OPSD). Includes time-series feature engineering, machine-learning baseline model, and production-ready API endpoints.
python docker machine-learning time-series opendata energy-consumption mlops energy-forecasting fastapi energy-forecasting-model mlops-project climate-tech
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Feb 2, 2026 - Python
Research and engineering platform for battery health, probabilistic energy forecasting, microgrid digital twins, scenario analysis, and uncertainty-aware dispatch optimization.
optimization digital-twin battery-health scientific-machine-learning energy-forecasting-model physics-informed-machine-learning
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Aug 15, 2026 - Jupyter Notebook
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