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https://github.com/nsswifter/solarpowergenerationanalysis
Machine learning analysis for predicting solar power generation using weather and sensor data from solar plants. This project leverages historical data and machine learning to improve the efficiency of renewable energy systems by optimizing solar energy forecasting.
https://github.com/nsswifter/solarpowergenerationanalysis
Last synced: 7 days ago
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Machine learning analysis for predicting solar power generation using weather and sensor data from solar plants. This project leverages historical data and machine learning to improve the efficiency of renewable energy systems by optimizing solar energy forecasting.
- Host: GitHub
- URL: https://github.com/nsswifter/solarpowergenerationanalysis
- Owner: nsswifter
- License: mit
- Created: 2024-11-09T21:42:08.000Z (7 days ago)
- Default Branch: main
- Last Pushed: 2024-11-09T21:58:30.000Z (7 days ago)
- Last Synced: 2024-11-09T22:32:30.648Z (7 days ago)
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# ⚡ Solar Power Generation Analysis
This project aims to accurately forecast solar power generation using historical weather data and solar panel output data. Solar energy prediction helps in efficient grid management, balancing supply and demand, and enhancing the integration of renewable energy sources.
## Dataset
The data used in this project is from the [Solar Power Generation Data](https://www.kaggle.com/datasets/anikannal/solar-power-generation-data) on Kaggle. This dataset includes weather and power output information from two solar plants.
## Installation
To run this project, you will need:
- Python 3.7+
- Jupyter Notebook
- Dependencies listed in [requirements.txt](requirements.txt)
Install the dependencies:
```bash
pip install -r requirements.txt
```
## Usage
1. **Clone the repository**:
```bash
git clone https://github.com/nsswifter/SolarPowerGenerationAnalysis.git
cd SolarPowerGenerationAnalysis
```
2. **Run the Notebook**:
Open [solar_power_generation_analysis.ipynb](solar_power_generation_analysis.ipynb) in Jupyter Notebook.
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request or open an Issue if you find any bugs or have suggestions for improvements.
## License
This project is licensed under the [MIT License](LICENSE).