0
Discussion

Definition and Interpretation of Wind Farm Efficiency in Complex Terrain: A Discussion

[+] Author and Article Information
Davide Astolfi

Department of Engineering,
University of Perugia,
Via G. Duranti 93,
Perugia, 06125, Italy
e-mail: davide.astolfi@unipg.it

Francesco Castellani

Department of Engineering,
University of Perugia,
Via G. Duranti 93,
Perugia, 06125, Italy
e-mail: francesco.castellani@unipg.it

Ludovico Terzi

Renvico srl.,
Via San Gregorio 34,
Milano, 20124, Italy
e-mail: ludovico.terzi@renvico.it

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received May 15, 2018; final manuscript received December 31, 2018; published online January 18, 2019. Assoc. Editor: Christopher Niezrecki.

J. Energy Resour. Technol 141(5), 055501 (Jan 18, 2019) (7 pages) Paper No: JERT-18-1344; doi: 10.1115/1.4042447 History: Received May 15, 2018; Revised December 31, 2018

The exploitation of wind turbines in complex terrain has recently been growing. The comprehension of wind flow, especially in the downstream area, is by itself a challenging task in complex terrain: even more so, it is difficult to account for the mixing between terrain effects and the wake interactions between nearby turbines. Efficiency is one of the simplest and meaningful metrics for quantifying the impact of wakes on wind farm production, but its definition is well established basically only for offshore wind farms. In this work, the definition of wind farm efficiency is, therefore, discussed, based on the critical points arising in complex terrain, where there can be at the same time a considerable variation of free wind flow along the layout and a directional distortion of the wakes, induced by the terrain. In this work, operational data of a test case wind farm sited in a very complex terrain, featuring 17 multimegawatt wind turbines, are elaborated and inspire a discussion and a novel definition of efficiency, that restores in the complex terrain case the meaning of the efficiency.

FIGURES IN THIS ARTICLE
<>
Copyright © 2019 by ASME
Your Session has timed out. Please sign back in to continue.

References

Amano, R. S. , 2017, “ Review of Wind Turbine Research in 21st Century,” ASME J. Energy Resour. Technol., 139(5), p. 050801. [CrossRef]
Cheng, P. W. , 2013, Transition to Renewable Energy Systems, Stolten, D., and Viktor, I., eds., Wiley, Hoboken, NJ, pp. 241–264.
Alfredsson, P. , and Segalini, A. , 2017, “ Wind Farms in Complex Terrains: An Introduction,” Philos. Trans. R. Soc. A: Math., Phys. Eng. Sci., 375(2091), p. 6. https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2016.0096
Hyvärinen, A. , and Segalini, A. , 2017, “ Effects From Complex Terrain on Wind-Turbine Performance,” ASME J. Energy Resour. Technol., 139(5), p. 051205.
Bitsuamlak, G. , Stathopoulos, T. , and Bédard, C. , 2004, “ Numerical Evaluation of Wind Flow Over Complex Terrain: Review,” J. Aerosp. Eng., 17(4), pp. 135–145. [CrossRef]
Blocken, B. , van der Hout, A. , Dekker, J. , and Weiler, O. , 2015, “ CFD Simulation of Wind Flow Over Natural Complex Terrain: Case Study With Validation by Field Measurements for Ria de Ferrol, Galicia, Spain,” J. Wind Eng. Ind. Aerodyn., 147, pp. 43–57. [CrossRef]
Dhunny, A. , Lollchund, M. , and Rughooputh, S. , 2017, “ Wind Energy Evaluation for a Highly Complex Terrain Using Computational Fluid Dynamics (CFD),” Renewable Energy, 101, pp. 1–9. [CrossRef]
Porté-Agel, F. , Wu, Y.-T. , Lu, H. , and Conzemius, R. J. , 2011, “ Large-Eddy Simulation of Atmospheric Boundary Layer Flow Through Wind Turbines and Wind Farms,” J. Wind Eng. Ind. Aerodyn., 99(4), pp. 154–168. [CrossRef]
Iungo, G. V. , Santhanagopalan, V. , Ciri, U. , Viola, F. , Zhan, L. , Rotea, M. A. , and Leonardi, S. , 2018, “ Parabolic Rans Solver for Low-Computational-Cost Simulations of Wind Turbine Wakes,” Wind Energy, 21(3), pp. 184–197. [CrossRef]
El-Asha, S. , Zhan, L. , and Iungo, G. V. , 2017, “ Quantification of Power Losses Due to Wind Turbine Wake Interactions Through Scada, Meteorological and Wind Lidar Data,” Wind Energy, 20(11), pp. 1823–1839. [CrossRef]
Barthelmie, R. , Hansen, K. , and Pryor, S. , 2013, “ Meteorological Controls on Wind Turbine Wakes,” Proc. IEEE, 101(4), pp. 1010–1019. [CrossRef]
Hansen, K. , Barthelmie, R. , Jensen, L. , and Sommer, A. , 2012, “ The Impact of Turbulence Intensity and Atmospheric Stability on Power Deficits Due to Wind Turbine Wakes at Horns Rev Wind Farm,” Wind Energy, 15(1), pp. 183–196. [CrossRef]
Al Sam, A. , Szasz, R. , and Revstedt, J. , 2017, “ An Investigation of Wind Farm Power Production for Various Atmospheric Boundary Layer Heights,” ASME J. Energy Resour. Technol., 139(5), p. 051216. [CrossRef]
McKay, P. , Carriveau, R. , and Ting, D. S.-K. , 2013, “ Wake Impacts on Downstream Wind Turbine Performance and Yaw Alignment,” Wind Energy, 16(2), pp. 221–234. [CrossRef]
Gebraad, P. , Teeuwisse, F. , Wingerden, J. , Fleming, P. A. , Ruben, S. , Marden, J. , and Pao, L. , 2016, “ Wind Plant Power Optimization Through Yaw Control Using a Parametric Model for Wake Effects a CFD Simulation Study,” Wind Energy, 19(1), pp. 95–114. [CrossRef]
Fleming, P. , Gebraad, P. M. , Lee, S. , Wingerden, J.-W. , Johnson, K. , Churchfield, M. , Michalakes, J. , Spalart, P. , and Moriarty, P. , 2015, “ Simulation Comparison of Wake Mitigation Control Strategies for a Two-Turbine Case,” Wind Energy, 18(12), pp. 2135–2143. [CrossRef]
Uemura, Y. , Tanabe, Y. , Mamori, H. , Fukushima, N. , and Yamamoto, M. , 2017, “ Wake Deflection in Long Distance From a Yawed Wind Turbine,” ASME J. Energy Resour. Technol., 139(5), p. 051212. [CrossRef]
Subramanian, B. , Chokani, N. , and Abhari, R. , 2016, “ Aerodynamics of Wind Turbine Wakes in Flat and Complex Terrains,” Renewable Energy, 85, pp. 454–463. [CrossRef]
Hansen, K. S. , Larsen, G. C. , Menke, R. , Vasiljevic, N. , Angelou, N. , Feng, J. , Zhu, W. J. , Vignaroli, A. , Xu, C. , and Shen, W. Z. , 2016, “ Wind Turbine Wake Measurement in Complex Terrain,” J. Phys.: Conf. Ser., 753, p. 032013. [CrossRef]
Castellani, F. , Astolfi, D. , Mana, M. , Piccioni, E. , Becchetti, M. , and Terzi, L. , 2017, “ Investigation of Terrain and Wake Effects on the Performance of Wind Farms in Complex Terrain Using Numerical and Experimental Data,” Wind Energy, 20(7), pp. 1277–1289. https://onlinelibrary.wiley.com/doi/abs/10.1002/we.2094
Astolfi, D. , Castellani, F. , and Terzi, L. , 2018, “ A Study of Wind Turbine Wakes in Complex Terrain Through RANS Simulation and Scada Data,” ASME J. Sol. Energy Eng., 140(3), p. 031001. [CrossRef]
Barthelmie, R. , Pryor, S. , Frandsen, S. , Hansen, K. , Schepers, J. , Rados, K. , Schlez, W. , Neubert, A. , Jensen, L. , and Neckelmann, S. , 2010, “ Quantifying the Impact of Wind Turbine Wakes on Power Output at Offshore Wind Farms,” J. Atmos. Oceanic Technol., 27(8), pp. 1302–1317. [CrossRef]
Castellani, F. , Astolfi, D. , Terzi, L. , Hansen, K. , and Rodrigo, J. , 2014, “ Analysing Wind Farm Efficiency on Complex Terrains,” J. Phys.: Conf. Ser., 524, p. 012142. [CrossRef]
Segalini, A. , and Castellani, F. , 2017, “ Wind-Farm Simulation Over Moderately Complex Terrain,” J. Phys.: Conf. Ser., 854, p. 012042.
Segalini, A. , 2017, “ Linearized Simulation of Flow Over Wind Farms and Complex Terrains,” Philos. Trans. R. Soc. A, 375(2091), p. 20160099. [CrossRef]
Ebenhoch, R. , Muro, B. , Dahlberg, J.-Å. , Berkesten Hägglund, P. , and Segalini, A. , 2017, “ A Linearized Numerical Model of Wind-Farm Flows,” Wind Energy, 20(5), pp. 859–875. [CrossRef]
Castellani, F. , Astolfi, D. , Burlando, M. , and Terzi, L. , 2015, “ Numerical Modelling for Wind Farm Operational Assessment in Complex Terrain,” J. Wind Eng. Ind. Aerodyn., 147, pp. 320–329. [CrossRef]

Figures

Grahic Jump Location
Fig. 3

The wind direction rose of WF1 at reference wind turbine: frequency distribution

Grahic Jump Location
Fig. 4

The wind direction rose of WF2 at reference wind turbine: frequency distribution

Grahic Jump Location
Fig. 5

Efficiency (according to Eq. (2)) of WF1 as a function of average nacelle position along the wind farm

Grahic Jump Location
Fig. 6

The distribution of efficiency measurements (according to Eq. (2)) for WF1

Grahic Jump Location
Fig. 7

The difference Δ of wind turbine average nacelle wind speed with respect to wind farm average, in units of standard deviation

Grahic Jump Location
Fig. 8

Efficiency of WF1 (according to Eq. (3)) and of WF2, as a function of wind direction at reference wind turbine

Grahic Jump Location
Fig. 9

Efficiency of WF1 (according to Eq. (3)) and of WF2, as a function of nacelle wind speed at reference wind turbine

Grahic Jump Location
Fig. 10

Efficiency of WF1 (according to Eq. (3)) as a function of wind direction and nacelle wind speed at reference wind turbine

Grahic Jump Location
Fig. 11

Efficiency of WF2 as a function of wind direction and nacelle wind speed at reference wind turbine

Tables

Errata

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In