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| title: Time Series Forecasting - ERCOT Electricity Market | |
| emoji: ⚡ | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: streamlit | |
| sdk_version: 1.52.1 | |
| app_file: app.py | |
| pinned: false | |
| python_version: 3.11 | |
| # Time Series Forecasting Application | |
| Zero-shot time series forecasting application for **ERCOT electricity market data** using state-of-the-art pretrained models. | |
| ## Features | |
| - ⚡ **Live ERCOT Data**: Fetches real-time electricity price data from ERCOT Day-Ahead Market (180+ days) | |
| - 🤖 **Multiple Models**: Choose from 7 pretrained forecasting models: | |
| - **Chronos-2** (46M - 120M parameters) - Amazon's latest models | |
| - **Chronos-T5** (8M - 710M parameters) - Original Chronos family | |
| - **TiRex** (35M parameters) - NX-AI's xLSTM-based model | |
| - 📊 **Backtesting**: Automatic train/test split with performance metrics (MAE, RMSE, MAPE) | |
| - 📈 **Interactive Visualization**: Historical context, actual values, and forecasts with date-based axes | |
| - 🎯 **Zero-Shot Forecasting**: No training required - models work out-of-the-box | |
| - 💻 **Easy-to-Use Interface**: Built with Streamlit for intuitive interaction | |
| ## Usage | |
| 1. Select a forecasting model from the dropdown | |
| 2. Choose data source (ERCOT or sample data) | |
| 3. Set the forecast horizon (number of time steps) | |
| 4. View backtesting results with error metrics and comparison plots | |
| ## Models | |
| ### Chronos-2 | |
| Amazon's latest time series foundation models offering state-of-the-art zero-shot forecasting performance. | |
| ### Chronos-T5 | |
| Original Chronos family based on T5 architecture, available in multiple sizes for different accuracy/speed tradeoffs. | |
| ### TiRex | |
| NX-AI's xLSTM-based model optimized for both short and long-term forecasting with excellent benchmark performance. | |
| ## Data Source | |
| - **ERCOT**: Day-Ahead Market Settlement Point Prices (SPP) from the Electric Reliability Council of Texas | |
| - **Sample Data**: Synthetic electricity price data for testing | |
| ## Links | |
| - [Chronos Forecasting](https://github.com/amazon-science/chronos-forecasting) | |
| - [TiRex Model](https://huggingface.co/NX-AI/TiRex) | |
| - [ERCOT Data](http://www.ercot.com/) |