Wind plant power optimization through yaw control using a parametric model for wake effects-a CFD simulation study

TLDR

The study proposes a wind‑plant control strategy that optimizes turbine yaw settings to enhance overall energy output by accounting for wake interactions. The controller uses the FLORIS parametric wake model, which predicts steady‑state wake positions, flow velocities, and turbine power as functions of axial induction and yaw, with its few parameters calibrated from power data. CFD simulations of a small wind farm show that FLORIS‑based yaw optimization raises plant energy production and simultaneously reduces turbine loads. © 2014 John Wiley & Sons, Ltd.

Abstract

This article presents a wind plant control strategy that optimizes the yaw settings of wind turbines for improved energy production of the whole wind plant by taking into account wake effects. The optimization controller is based on a novel internal parametric model for wake effects called the FLOw Redirection and Induction in Steady-state (FLORIS) model. The FLORIS model predicts the steady-state wake locations and the effective flow velocities at each turbine, and the resulting turbine electrical energy production levels, as a function of the axial induction and the yaw angle of the different rotors. The FLORIS model has a limited number of parameters that are estimated based on turbine electrical power production data. In high-fidelity computational fluid dynamics simulations of a small wind plant, we demonstrate that the optimization control based on the FLORIS model increases the energy production of the wind plant, with a reduction of loads on the turbines as an additional effect. Copyright © 2014 John Wiley & Sons, Ltd.