Client
A mid-sized renewable energy producer operating solar and wind assets across Europe and North America.
Challenge
The client faced challenges in forecasting generation and pricing contracts effectively due to the volatility of renewable sources and market fluctuations. Their existing ETRM systems lacked advanced analytics, leading to suboptimal hedging decisions and reduced profitability.
Solution
- Renewable Forecasting Models: Used machine learning to integrate weather data and historical generation for predictive accuracy.
- Price Forecasting Engine: Built time-series models to predict power market prices using market data and external drivers.
- P&L Simulation Dashboards: Developed interactive tools for evaluating hedging strategies and exposure.
- Scenario Analysis: Enabled stress-testing under regulatory, climate, and demand fluctuations.
Technologies Used
- Python (Scikit-learn, XGBoost), Azure ML
- Snowflake for data warehousing
- Power BI for interactive visualization
- Integration with Endur and custom ETRM systems via REST APIs
Impact
- 28% improvement in generation forecast accuracy
- 15% increase in gross margin from energy trading
- Real-time dashboards empowered traders with better visibility and faster decisions
- Supported ESG goals with improved grid-aligned forecasting
Client Testimonial
“Durga Analytics helped transform our trading desk into a data-driven decision hub. The integration of weather-aware forecasting into our pricing models has been a game-changer.”