Special Issue "Fast-Running Engineering Models of Wind Farm Flows"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "B2: Wind, Wave and Tidal Energy".

Deadline for manuscript submissions: 31 January 2022.

Special Issue Editors

Dr. Majid Bastankhah
E-Mail Website
Guest Editor
Department of Engineering, Durham University, Durham DH1 3LE, UK
Interests: wind energy aerodynamics; physics-based engineering wake models; experimental fluid mechanics; turbulent flows
Dr. Ervin Bossanyi
E-Mail Website
Guest Editor
1. Faculty of Engineering, Bristol University, Bristol BS8 1TS, UK
2. DNV, One Linear Park, Avon Street, Bristol BS2 0PS, UK
Interests: renewable energy technologies; grid integration; wind engineering; wind energy; wind turbines; wind farms; control; simulation; wind power and power systems
Dr. Dries Allaerts
E-Mail Website
Guest Editor
Faculty of Aerospace Engineering, Delft University of Technology, Kluyverweg 1, 2629 HS Delft, The Netherlands
Interests: wind farm aerodynamics; wake aerodynamics; boundary-layer meteorology; atmospheric gravity waves; computational fluid dynamics; engineering models

Special Issue Information

Dear Colleagues,

Despite the rapid growth of flow measurement technologies and numerical simulation techniques over the last few decades, fast-running engineering models are still the most popular tools in industry to characterise and predict wind farm flows. This is mainly due to their low computational costs and ease of use. These models, which can be empirical or physics-based, cover a wide range of topics including but not limited to:

  • Turbine wake flows: mean flow (steady or dynamic) and turbulence characteristics, wake meandering, wake recovery, near-wake to far-wake transition, wake deflection, etc.;
  • Cumulative wake effects: wake superposition techniques;
  • Load estimation: steady and unsteady distribution of loads on wind turbine blades and other turbine components, blade element momentum theory (BEM), fatigue due to turbulence, and wake immersion, etc.;
  • Flow blockage: velocity reduction upwind of wind turbines and wind farms, and flow speed-up (i.e., jetting) between adjacent wind turbine columns in a wind farm;
  • Topography and wind farms: impact of hills, forests, and human-made objects on the performance of wind turbines and wind farms;
  • Wind farm power production: effect of atmospheric turbulence or layout configuration on power generation, and power unsteadiness caused by turbulence, etc.;
  • Wind farm control: influencing wake effects and blockage by adjusting the control of individual turbines;
  • Wind farm interaction with the atmospheric boundary layer: top-down models, growth of the internal boundary layer, concept of infinite (i.e., very large) wind farms, wind-farm-induced atmospheric gravity waves, wind farm wakes and farm–farm interactions, etc.;
  • Thermal stability and Coriolis force: effect of thermal stratification on performance of wind farms, low-level jets, wind veer, and wind shear, etc.

The aim of this Special Issue is to gather new original research either on the development of new fast-running engineering models or the application of existing models in different fields of wind energy research mentioned above, and beyond.

Dr. Majid Bastankhah
Dr. Ervin Bossanyi
Dr. Dries Allaerts
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Fast-running model
  • Analytical model
  • Physics-based model
  • Control-oriented model
  • Wind turbine
  • Wind farm
  • Wake
  • Active wake control
  • Wind farm flow control
  • Turbine power generation
  • Wake superposition
  • Cumulative wake effect
  • Wake meandering
  • Wake turbulence
  • Flow blockage
  • Thermal stability
  • Atmospheric boundary layer
  • Coriolis force
  • Wind veer
  • Wind shear
  • Topography
  • Internal boundary layer
  • Infinite wind farm
  • Atmospheric gravity waves

Published Papers

This special issue is now open for submission, see below for planned papers.

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Comparison of the Gaussian wind farm model with historical data of three offshore wind farms
Authors: B.M. Doekemeijer, E. Simley and P.A. Fleming
Affiliation: National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
Abstract: Model validation remains one of the largest barriers for wind farm control deployment. The Gaussian-shaped wake model has grown in popularity, yet validation remains limited. This article addresses this scientific gap, providing a model comparison of the Gaussian farm model with historical data of three offshore wind farms. Results show that the Gaussian model is very accurate for arrays up to 3-4 turbines deep with accurate wake widths and depths for most turbine sets. Two weaknesses in the model are the underestimation of wake depth in large turbine arrays, and the underestimation of wake depth in arrays with large inter-turbine spacings. Future work will address these weaknesses.

Title: On the Wake Growth Rate of a Porous Disc Immersed in a Boundary Layer
Authors: Anas Abdulrahim, Abdelrahman Hassanein, Tugrul Akpolat, Mustafa Percin, Oguz Uzol
Affiliation: METU Center for Wind Energy Research
Abstract: In wind tunnel studies, wind turbine wakes are frequently modeled using porous discs because of their design simplicity and cost efficiency. This paper presents the results of an experimental investigation focusing on the wake growth rate characteristics of a radially non-uniform porous disc as it is immersed in a boundary layer inflow. Estimation of the wake growth rate is critical for engineering wake models to predict the wake velocity profiles of wind turbines operating in wind farms. The results show that the wake growth rate of the porous disc can be significantly higher than those estimated through empirical relations suggested in the literature in the context of engineering wake models, particularly at low ambient turbulence conditions. This suggests caution in the use of porous discs to simulate wind turbine wakes and wind farms in wind tunnel studies. The manuscript will present comparisons of measured porous disc wake velocity fields with those predicted by Bastankhah-Porte Agel and Ishihara-Qian wake models illustrating the deviations especially due to high k* levels of the porous disc.

Title: RANS Based Wake Prediction for Wind Turbines: A Comparative Study with Experiments and Engineering Wake Models
Authors: Ali Ata Adam, Olcay Nurtac Deniz, Nilay Sezer-Uzol, Oguz Uzol
Affiliation: METU Center for Wind Energy Research
Abstract: Both analytical and numerical wake models are generally used to predict wake related losses in the design and optimization of wind farms layouts. Although analytical models are computationally very low-cost, they lack the ability to predict complex interactions that occur in a wind farm configuration. RANS based CFD simulations provide a better alternative to engineering wake models and they are less costly compared to LES based computations. However, the performance of RANS simulations heavily depend on the performance of turbulence modeling used. This paper presents an extensive comparative study using the results of RANS simulations with 4 different turbulence and 2 different transition models to predict the wakes of single and tandem wind turbine configurations in a wind tunnel operating under two different inflow turbulence conditions (i.e. 0.23% and 10%). The predictions are compared with experimental data and with the predictions of a variety of engineering wake models. In addition, RANS predicted wake growth rates obtained using different turbulence and transition models are compared with those obtained using different engineering wake models for single turbine configuration and also RANS predictions downstream of the second turbine are compared with various analytical wake superposition methods defined in the literature for tandem turbine configuration.

Title: Validation of engineering blockage models for wind farm flows with RANS and wind tunnel measurements
Authors: Alexander Meyer Forsting (1), Gonzalo Navarro Diaz (2), Antonio Segalini (2), Stefan Ivanell (2)
Affiliation: (1) DTU Wind Energy, Roskilde, Denmark; (2) Uppsala University, Campus Gotland, Sweden
Abstract: Fast engineering wake models are the backbone of wind farm AEP estimators, whereas the addition of induction zone models in existing tools is a more recent response to rising concerns over wind farm blockage associated losses. Unlike the term might suggest, blockage is not a pure energy sink, but also redistributes momentum, enhancing power variation throughout a wind farm. With RANS simulations and wind tunnel measurements of certain blockage-focused test cases we validate the existing blockage models available in PyWake by comparing the velocity fields and power production.

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