Abstract

Abstract. Wind turbines are often sited together in wind farms as it is economically advantageous. Controlling the flow within wind farms to reduce the fatigue loads, maximize energy production and provide ancillary services is a challenging control problem due to the underlying time-varying non-linear wake dynamics. In this paper, we present a control-oriented dynamical wind farm model called the WindFarmSimulator (WFSim) that can be used in closed-loop wind farm control algorithms. The three-dimensional Navier–Stokes equations were the starting point for deriving the control-oriented dynamic wind farm model. Then, in order to reduce computational complexity, terms involving the vertical dimension were either neglected or estimated in order to partially compensate for neglecting the vertical dimension. Sparsity of and structure in the system matrices make this model relatively computationally inexpensive. We showed that by taking the vertical dimension partially into account, the estimation of flow data generated with a high-fidelity wind farm model is improved relative to when the vertical dimension is completely neglected in WFSim. Moreover, we showed that, for the study cases considered in this work, WFSim is potentially fast enough to be used in an online closed-loop control framework including model parameter updates. Finally we showed that the proposed wind farm model is able to estimate flow and power signals generated by two different 3-D high-fidelity wind farm models.

Highlights

  • Optimizing the control of wind turbines in a farm is challenging due to the aerodynamic interactions among turbines

  • We present a control-oriented dynamical wind farm model called the WindFarmSimulator (WFSim) that can be used in closed-loop wind farm control algorithms

  • We showed that by taking the vertical dimension partially into account, the estimation of flow data generated with a high-fidelity wind farm model is improved relative to when the vertical dimension is completely neglected in WFSim

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Summary

Introduction

Optimizing the control of wind turbines in a farm is challenging due to the aerodynamic interactions among turbines. Considered as medium-fidelity models are the ones presented in Boersma et al (2016b) and Soleimanzadeh et al (2014) These wind farm models are based on the discretized 2-D Navier–Stokes equations. The dynamic control-oriented wind farm model presented in this paper, referred to as WindFarmSimulator (WFSim), is applicable in the framework discussed above and satisfies the two points above. It is based on corrected 2-D Navier–Stokes equations and contains a heuristic turbulence model. 3, WFSim will be validated in two cases using flow velocities in the longitudinal and lateral directions at hub height and turbine power signals computed with two different LES-based wind farm models.

Formulation of a dynamic control-oriented wind farm model
Turbulence model
Turbine model
Discretization
Boundary and initial conditions
Computation time
Simulation results
Quality measures
Axial induction actuation
Conclusions
Discretizing the pressure gradient
Discretizing the Continuity equation
Full Text
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