{"id":19237664,"url":"https://github.com/adamouization/solar-irradiance-forecasting","last_synced_at":"2026-05-06T00:06:05.444Z","repository":{"id":193144170,"uuid":"680043298","full_name":"Adamouization/Solar-Irradiance-Forecasting","owner":"Adamouization","description":"Predicting short-term solar irradiance using deep learning and statistical methods on the Folsom dataset","archived":false,"fork":false,"pushed_at":"2023-09-07T10:23:21.000Z","size":4999,"stargazers_count":0,"open_issues_count":1,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-09-08T23:51:38.412Z","etag":null,"topics":["arima","arima-forecasting","data-science","deep-learning","irradiance","irradiance-forecasting","machine-learning","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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issues](https://img.shields.io/github/issues/Adamouization/Solar-Irradiance-Forecasting) [![License: AGPL v3](https://img.shields.io/badge/License-AGPL_v3-blue.svg)](https://www.gnu.org/licenses/agpl-3.0)\n\n![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54) ![Jupyter Notebook](https://img.shields.io/badge/jupyter-%23FA0F00.svg?style=for-the-badge\u0026logo=jupyter\u0026logoColor=white) ![Keras](https://img.shields.io/badge/Keras-%23D00000.svg?style=for-the-badge\u0026logo=Keras\u0026logoColor=white) ![TensorFlow](https://img.shields.io/badge/TensorFlow-%23FF6F00.svg?style=for-the-badge\u0026logo=TensorFlow\u0026logoColor=white) ![Pandas](https://img.shields.io/badge/pandas-%23150458.svg?style=for-the-badge\u0026logo=pandas\u0026logoColor=white) ![NumPy](https://img.shields.io/badge/numpy-%23013243.svg?style=for-the-badge\u0026logo=numpy\u0026logoColor=white) ![Matplotlib](https://img.shields.io/badge/Matplotlib-%23ffffff.svg?style=for-the-badge\u0026logo=Matplotlib\u0026logoColor=black) ![scikit-learn](https://img.shields.io/badge/scikit--learn-%23F7931E.svg?style=for-the-badge\u0026logo=scikit-learn\u0026logoColor=white)\n\n___\n\n\n## Project Goal\n\nSolar energy is a rapidly growing source of renewable energy, contributing significantly to global sustainability efforts. It depends on solar irradiance, which is the amount of solar energy received per unit area, measured using GHI (global irradiance). Accurate solar irradiance forecasting is crucial for:\n* optimising energy production\n* designing, planning and operational management of solar energy farms.\n\nThe goal of this project is to build a predictive model that can accurately predict future irradiance.\n\nThe objective is to leverage the various historical data provided in the *\"[A comprehensive dataset for the accelerated development and benchmarking of solar forecasting methods](https://zenodo.org/record/2826939)\"* dataset to build a solution that can accurately forecast irradiance for the next 20 minutes.\n\n## Preliminary LSTM result\n\n![image](https://raw.githubusercontent.com/Adamouization/Solar-Irradiance-Forecasting/master/output/model_validation/lstm_v4_forecast_vs_actual.png)\n\n## Setup\n\nCreate a virtual environment:\n\n```\npython -m venv \u003cPATH\u003e/Solar-Irradiance-Forecasting\nsource \u003cPATH\u003e/Solar-Irradiance-Forecasting/bin/activate\n```\n\nInstall requirements:\n\n```\ncd Solar-Irradiance-Forecasting\npip install -r env/requirements-light.txt\n```\n\nDownload data:\n```\npython src/utils/donwload_zenodo_data.py\n```\n\nOpen relevant Jupyternotebooks in `src/`\n\n## License \n* see [LICENSE](https://github.com/Adamouization/Solar-Irradiance-Forecasting/blob/master/LICENSE) file.\n\n## Contact\n* Email: adam[at]jaamour[dot]com\n* Website: www.adam.jaamour.com\n* Linktree: https://linktr.ee/adamouization\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadamouization%2Fsolar-irradiance-forecasting","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fadamouization%2Fsolar-irradiance-forecasting","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadamouization%2Fsolar-irradiance-forecasting/lists"}