Stochastic model predictive controller for wind farm frequency regulation in waked conditions

摘要

? 2022 Elsevier B.V.As renewable energy penetrations increase, wind farms may be required to provide ancillary services such as frequency regulation. For wind farms, two issues complicate frequency regulation: turbine-wake interactions alter the available wind power, and the future power reference signal is uncertain. This paper presents a stochastic model predictive controller (MPC) for wind farms to track an uncertain frequency regulation signal while accounting for wakes. The controller uses a simplified Park model with wake propagation delay to predict turbine-wake interactions. The controller operates without any knowledge of the future power regulation signal or wind speed. The controller solves a nonconvex stochastic optimization program using scenario optimization. Our stochastic MPC tracks with 7–10 less error than our deterministic MPC controllers.