Simplified wake modelling for wind farm load prediction

Jacobus B De Vaal,Michael Muskulus

doi:10.1088/1742-6596/2018/1/012012

Abstract

This paper presents a simple numerical wind farm model, where pragmatic choices are made in the modelling of underlying physical processes, with the aim of making useful power production and wind turbine load estimates. The numerical model decomposes the wind farm, inspired by the approach of the dynamic wake meandering model (DWM), into simple sub-models for a single wake deficit (1D Gaussian), wake meandering (statistical), and wake added turbulence (eddy viscosity based). Particular attention is given to selecting a momentum conserving wake summation method, because of its critical role in coupling the influence of individual wakes. Results are presented to illustrate the influence that wake summation methods have on equilibrium velocity and power production in a row of turbines, for different inter-turbine spacing and inflow velocities. Comparisons against published data from the Lillgrund wind farm illustrate that the suggested modelling approach reproduces important trends observed in the field data.

Highlights

Making optimal use of available wind resources for renewable energy generation, implies extracting the highest possible power output, at lowest possible cost, minimizing the levelized cost of energy (LCOE)
To illustrate the significance that wake summation method has for a wind farm model, consider a farm consisting of eight in-line turbines, spaced 4.3 diameters apart
The results indicate that an upper bound for equilibrium velocity appears to be given by the summation method that considers only the single largest wake influence, U = U∞ − max (U∞ − ui)

Summary

Introduction

Making optimal use of available wind resources for renewable energy generation, implies extracting the highest possible power output, at lowest possible cost, minimizing the levelized cost of energy (LCOE). The wakes behind individual turbines influence both the power production and structural loads of wake affected turbines. The LCOE is directly influenced by wakes, and wake modelling plays an important role in wind farm design. The intention of some of these methods is only to give accurate estimates of power production, and as a consequence, the velocity fields they predict do not necessarily lead to accurate structural loads. For accurate prediction of structural load, aeroelastic simulations need to be performed, where the dynamic wake meandering (DWM) approach has proven to be very successful. Suggested [4] nearly two decades ago, the model has been continuously improved and adapted for aeroelastic simulations [5], and is included in design standards [6]

Methods

Results

Conclusion