Wind turbine wakes are one of the most important aspects in wind power meteorology because they decrease the power production and increase the loading of downstream wind turbines. Therefore, there is a continuous need to find a ‘good’ wake model to properly plan wind power plant-level control strategies, predict the performance and understand the fatigue loads of turbines. In this paper, six widely used approaches of wake modelling (Jensen, Larsen, Dynamic Wake Meandering, Fuga and, Ellipsys3D LES and RANS together with their interpretations) that were developed at Technical University of Denmark, are described and the model subcomponents are analysed. The models are evaluated using data from the Sexbierum (onshore) and the Lillgrund (offshore) wind farms to understand how to best utilize them.The paper provides a comprehensive conceptual background to wake modelling combined with the overview of the state-of-the-art models including their implementations on operating wind farms

This article presents a review of the state of the art of the Wind Farm Design and Optimization (WFDO) problem. The WFDO problem refers to a set of advanced planning actions needed to extremize the performance of wind farms, which may be composed of a few individual Wind Turbines (WTs) up to thousands of WTs. The WFDO problem has been investigated in different scenarios, with substantial differences in main objectives, modelling assumptions, constraints, and numerical solution methods. The aim of this paper is: (1) to present an exhaustive survey of the literature covering the full span of the subject, an analysis of the state-of-the-art models describing the performance of wind farms as well as its extensions, and the numerical approaches used to solve the problem; (2) to provide an overview of the available knowledge and recent progress in the application of such strategies to real onshore and offshore wind farms; and (3) to propose a comprehensive agenda for future research.

This paper gives an evaluation of most of the commonly used models for predicting wind speed decrease (wake) downstream of a wind turbine. The evaluation is based on six experiments where free-stream and wake wind speed profiles were measured using a ship-mounted sodar at a small offshore wind farm. The experiments were conducted at varying distances between 1.7 and 7.4 rotor diameters downstream of the wind turbine. Evaluation of the models compares the predicted and observed velocity deficits at hub height. A new method of evaluation based on determining the cumulative momentum deficit over the profiles is described. Despite the apparent simplicity of the experiments, the models give a wide range of predictions. Overall, it is not possible to establish any of the models as having individually superior performance with respect to the measurements.

This paper investigates wake effects on load and power production by using the dynamic wake meander (DWM) model implemented in the aeroelastic code HAWC2. The instationary wind farm flow characteristics are modeled by treating the wind turbine wakes as passive tracers transported downstream using a meandering process driven by the low frequent cross‐wind turbulence components. The model complex is validated by comparing simulated and measured loads for the Dutch Egmond aan Zee wind farm consisting of 36 Vestas V90 turbine located outside the coast of the Netherlands. Loads and production are compared for two distinct wind directions—a free wind situation from the dominating southwest and a full wake situation from northwest, where the observed turbine is operating in wake from five turbines in a row with 7D spacing. The measurements have a very high quality, allowing for detailed comparison of both fatigue and min–mean–max loads for blade root flap, tower yaw and tower bottom bending moments, respectively. Since the observed turbine is located deep inside a row of turbines, a new method on how to handle multiple wakes interaction is proposed. The agreement between measurements and simulations is excellent regarding power production in both free and wake sector, and a very good agreement is seen for the load comparisons too. This enables the conclusion that wake meandering, caused by large scale ambient turbulence, is indeed an important contribution to wake loading in wind farms. Copyright © 2012 John Wiley & Sons, Ltd.