Stochastic optimization based economic dispatch and interruptible load management with distributional forecast of wind farm generation

We study stochastic optimization of economic dispatch (ED) and interruptible load management using short-term distributional forecast of wind farm generation. Specifically, we develop a Markov-chain-based distributional forecast model for wind farm generation based on spatial and temporal characteristics of the wind turbine power output in a wind farm. Built on the distributional forecast model, the joint optimization of ED and interruptible load management is cast as a stochastic optimization problem. The proposed stochastic ED problem is compared with the deterministic ED problem using the persistence wind generation forecast model, and also with the scenario-based ED formulation which uses all possible wind generation states. Numerical studies, using a modified IEEE RTS 24-bus system and realistic wind measurement data from an actual wind farm, demonstrate the significant benefits obtained by leveraging the Markov-chain-based distributional forecast and the interruptible load management.