Scenario Generation of Wind Farm Power for Real-Time System Operation

Understand

This work proposes a method of wind farm scenario generation to support real-time optimization tools and presents key findings therein.

• This work draws upon work from the literature and presents an efficient and scalable method for producing an adequate number of scenarios for a large fleet of wind farms while capturing both spatial and temporal dependencies.
• The method makes probabilistic forecasts using conditional heteroscedastic regression for each wind farm and time horizon.
• Past training data is transformed (using the probabilistic forecasting models) into standard normal samples.