Engineering · tutorial
Power Generation Predictor
Estimate generation from operating conditions
What does this project try to do?
Estimate generation from operating conditions Load power-plant operating variables, train a regression baseline, and compare estimated output with observed output.
How does it work?
Load power-plant operating variables, train a regression baseline, and compare estimated output with observed output.
What will you learn?
Compare model predictions with measured generation and inspect errors.
How to run this project
Option A — Google Colab (recommended for beginners)
- Click Download Notebook (.ipynb) below. The file should download instead of displaying raw JSON.
- Open Google Colab.
- Choose File → Upload notebook → Browse and select the downloaded
.ipynb. - Run any dependency-install cell first, if present.
- Choose Runtime → Run all, or run cells individually with ▶.
- Review tables, charts and evaluation metrics. If a compatible real dataset is used, upload it to Colab and update the notebook file path.
Option B — Run on your computer
- Install Python 3 and enable Add Python to PATH.
- Open Command Prompt and run
pip install jupyterlab pandas numpy scikit-learn matplotlib openpyxl. - Open the folder containing the downloaded notebook.
- Run
jupyter lab. - Open the
.ipynbfile and choose Run → Run All Cells.
Open, run or download
These projects run locally in Python, Jupyter or a browser. There is no hosted execution server; “Run” means opening a browser demo where provided or following the local setup steps.
Educational demonstration only. Bundled sample data may be synthetic. Results have not been independently validated for industrial or cybersecurity deployment. Do not upload confidential project data.