EcoVolt is an AI-powered dashboard designed to help users forecast solar and wind energy investments based on real-time weather data, geographic location, and budget constraints. This dashboard provides energy generation forecasts using machine learning models trained on historical data.
Key Features Real-time weather-based energy prediction Location & budget input Interactive visualizations (Plotly charts, 3D Pydeck maps)
Tech stack: Backend: Python, Streamlit, SQLite Machine Learning: XGBoost, sklearn Visualization: Plotly Containerization: Docker Frontend: NextJS
Installation and Setup
- Clone the repository: git clone https://github.com/hackfest-dev/Hackfest25-35
- Build the Docker image: cd energy-forecast-dashboard docker build -t energy-forecast-dashboard .
- Run the Docker container: docker run -p 8501:8501 energy-forecast-dashboard
Frontend (Next.js) npm install npm run dev
The application will be available at http://localhost:8501.
Usage:
- Choose the energy type you want to view (wind, solar, or demand) by clicking the corresponding button in the Live Prediction Demo section.
- Select the Location and Budget.
- Observe the real-time predictions and insights provided by the dashboard.
- Utilize the chart visualizations to make informed decisions about energy strategies and resource potential.