| title | Electricity Grid Model |
|---|---|
| emoji | ⚡ |
| colorFrom | yellow |
| colorTo | red |
| sdk | gradio |
| app_port | 7860 |
| app_file | app.py |
| pinned | false |
Machine learning model for forecasting Australian electricity spot prices.
This repository contains the implementation of a pricing prediction model deployed on Hugging Face. It generates short-term forecasts for electricity prices based on historical and real-time data.
- Predicts spot prices at:
- 5 minutes
- 15 minutes
- 30 minutes
- Integrated with external APIs for live inference
- Deployable via Hugging Face Spaces
The model is hosted on Hugging Face and exposed via an API endpoint for inference.
- Time-series electricity data
- Market indicators
- Predicted spot prices for defined time horizons
This model integrates with:
- Electricity Grid API (data input)
- AWS Lambda (automated testing and triggering)
The model can be accessed via API calls or integrated into downstream applications such as dashboards or trading tools.
- Ensure input data is preprocessed consistently
- Model performance depends on data freshness