Develop and Evaluate Price Forecasting Model

Implement an advanced time-series forecasting model (e.g., LSTM, Transformer, or Prophet) to predict 15-minute electricity prices for a 24-48 hour horizon. Train and validate your model using the prepared historical data. Evaluate its performance using metrics like MAPE, RMSE, and MAE. Consider external factors such as weather data (temperature, solar irradiance, wind speed) or day-ahead market prices as features to improve accuracy. Containerize your forecasting model using Docker.