Model Predictive and Adaptive Control of Wind Farm Active Power Output

Abstract

In this chapter, we introduce a novel supervisory wind farm controller that enables the active power output of a wind farm to accurately and smoothly track a desired reference provided by a power grid operator. Developed based on the approximate wind turbine control systems model from Chap. 3, this wind farm controller has a two-loop architecture, consisting of an outer feedback loop and an inner one. The outer feedback loop contains a model predictive controller, which uses various forecasts and feedbacks to iteratively compute a set of desired power trajectories, so that the deterministic tracking accuracy of the wind farm power output on a receding horizon is optimized. In contrast, the inner feedback loop contains an adaptive controller, which uses estimated wind speed characteristics to adaptively tune a set of proportional controller gains, so that the stochastic smoothness of the wind farm power output on a shorter timescale is optimized. We also present a series of simulation studies that illustrate the salient features of the wind farm controller, including its ability to exploit forecast availability, design freedom, and wind speed correlation.