This project is an AI-based system that forecasts energy consumption using machine learning and provides interactive visualization through a Streamlit web application.
Energy demand is unpredictable, leading to:
- Power wastage
- High electricity costs
- Grid imbalance
- Increased carbon emissions
This project solves it using AI-based forecasting.
Used in:
- Smart Cities
- Power Grid Management
- Manufacturing Plants
- Data Centers
- Renewable Energy Systems
- Python
- Pandas, NumPy
- Scikit-learn
- Matplotlib
- Streamlit
- Household energy consumption dataset
- Time-series format
- Includes timestamp & usage values
Data → Preprocessing → Feature Engineering → Model → Forecast → Visualization
git clone https://github.com/YOUR_USERNAME/AI-Energy-Forecasting-System.git
cd AI-Energy-Forecasting-System
python -m venv venv
venv\Scripts\activate
pip install -r requirements.txtRun Streamlit app:
streamlit run app.py- Accurate energy forecasting
- RMSE & R² evaluation
- Interactive dashboard
- Time series forecasting
- ML pipeline design
- Feature engineering
- Streamlit deployment
- Real-world project building
- Deploy on cloud (Streamlit Cloud)
- Add real-time data
- Use LSTM / Deep Learning