ResPy is a Python-based toolkit designed to centralize and process power market data for advanced analysis, forecasting, and decision support in energy trading.
Its core purpose is to model and simulate a wide range of renewable assets—starting with solar and wind farms, and later extending to battery storage systems. ResPy also supports backtesting of hedging strategies and automated analytics workflows tailored for short-term electricity markets.
-
Asset Modeling
Simulate generation profiles and market behavior for RES assets (solar, wind, batteries). -
Backtesting Framework
Evaluate and optimize hedging strategies using historical market data. -
Price Forecasting
Build models to forecast Day-Ahead auction prices and forward products along the power curve. -
Automated Reporting
Automatically generate reports for DA auctions, including price trends, spreads, and asset performance. -
RES Forecasting
Predict renewable generation based on weather and historical data. -
Interactive Dashboards
Explore production, market signals, and forecasts through intuitive visual dashboards.
Displays daily renewable power generation in France over multiple years.
🔗 View dashboard
Compares the morning forecast (generated by ResPy) with the evening forecast from RTE and the actual realized RES power generation.
🔗 View dashboard
Shows the monthly capture rate for renewable assets in the French power market.
🔗 View dashboard
🔗 Future Day-Ahead Power Curve Documentation
🔗 Forward Power Curve Hourly Documentation
🔗 Capture Rate Evolution Analysis
Hugo Lambert – Energy Forecasting & Market Modeling
Feel free to reach out hugo.lambert.perso@gmail.com