🌞 Power Factor Prediction (PF PredictX) - Energizing Efficiency

Welcome to the PF PredictX project repository! This initiative, developed under the Digital Egypt Pioneers Initiative, harnesses the power of machine learning to revolutionize energy efficiency in electrical systems. Our mission is to predict power factor (PF) with precision, optimizing energy usage and reducing operational costs in residential and industrial settings. Powered by advanced algorithms like LSTM and Random Forest, this project lights the way toward a sustainable energy future!

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⚡ Main Goal

The core objective of PF PredictX is to leverage a large-scale dataset of power consumption trends to forecast power factor, a critical metric for energy efficiency. By identifying key predictors and deploying an interactive dashboard and web application, we aim to empower energy managers with real-time insights, minimizing losses and enhancing system reliability in the dynamic energy landscape.

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🔋 Requirements Installation

To get started with PF PredictX and tap into its energy potential, ensure you have the following dependencies installed:

• Python 3.10+: The backbone of our code (download from python.org).

• Required Libraries: Install via pip with the following command:

  pip install -r requirements.txt

  The requirements.txt file includes essential packages like:

  • scikit-learn for machine learning
  • tensorflow for LSTM implementation
  • flask for web deployment
  • matplotlib and pandas for visualization and data handling

• Git: For cloning and managing the repository (install from git-scm.com).

• LaTeX: For compiling the IEEE paper (optional, install TeX Live or equivalent).

• Render Service Account: For deploying the web application (sign up at render.com).

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💡 General Steps to Clone or Contribute

Cloning the Project

Energize your local machine by cloning this repository with these steps:

1. Open your terminal and navigate to your desired directory:

   cd ~/your/projects/folder

2. Clone the repository using SSH (recommended) or HTTPS:

   git clone [email protected]:Noorpr/Project-DEPI.git

   or

   git clone https://github.com/Noorpr/Project-DEPI.git

3. Move into the project directory:

   cd Project-DEPI

4. Install the requirements as outlined above.

Contributing via Pull Request

Power up the project with your contributions! Follow these steps to submit a pull request:

1. Fork the Repository: Click the "Fork" button on the GitHub page to create your own copy.
2. Create a Feature Branch:

   git checkout main
   git pull origin main
   git checkout -b feature/your-feature-name

3. Make Changes: Implement your improvements or fixes, then commit them:

   git add .
   git commit -m "Add your descriptive message here"

4. Push to Your Fork:

   git push origin feature/your-feature-name

5. Submit a Pull Request: Go to the GitHub page, click "New Pull Request," and describe your changes. Our team will review and merge your energy-boosting contribution!

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🌍 Let's Power the Future Together!

Join us in illuminating the path to energy efficiency! Explore the code, check out the IEEE paper for technical details, and deploy the web app using Render. For questions or collaboration, feel free to open an issue or reach out.

🔋 Stay Charged, Stay Efficient!