Effects of Onshore and Offshore Environmental Parameters on the Leading Edge Erosion of Wind Turbine Blades: A Comparative Study

Verma, Amrit Shankar; Jiang, Zhiyu; Ren, Zhengru; Hu, Weifei; Teuwen, Julie J.E.

doi:10.1115/1.4049248

Cited by 8 publications

(5 citation statements)

References 31 publications

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“…Note that this assumption may underestimate the lifetime calculated for the wind turbines installed at the coastal sites as shown in Verma et al 14 and Shankar Verma et al, 36 but it shouldn't affect the main findings and conclusions of the paper. Figure 5 presents the probability density function (PDF) of droplet size for different rain intensities (

I = 0.1

, 1, 10, 25 mm/h) using Best's DSD.…”

Section: Methodology and Case Studymentioning

confidence: 93%

A probabilistic long‐term framework for site‐specific erosion analysis of wind turbine blades: A case study of 31 Dutch sites

et al. 2021

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Rain‐induced leading‐edge erosion (LEE) of wind turbine blades (WTBs) is associated with high repair and maintenance costs. The effects of LEE can be triggered in less than 1 to 2 years for some wind turbine sites, whereas it may take several years for others. In addition, the growth of erosion may also differ for different blades and turbines operating at the same site. Hence, LEE is a site‐ and turbine‐specific problem. In this paper, we propose a probabilistic long‐term framework for assessing site‐specific lifetime of a WTB coating system. Case studies are presented for 1.5 and 10 MW wind turbines, where geographic bubble charts for the leading‐edge lifetime and number of repairs expected over the blade's service life are established for 31 sites in the Netherlands. The proposed framework efficiently captures the effects of spatial and orographic features of the sites and wind turbine specifications on LEE calculations. For instance, the erosion is highest at the coastal sites and for sites located at higher altitudes. In addition, erosion is faster for turbines associated with higher tip speeds, and the effects are critical for such sites where the exceedance probability for rated wind conditions are high. The study will aid in the development of efficient operation and maintenance strategies for wind farms.

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I = 0.1

, 1, 10, 25 mm/h) using Best's DSD.…”

Section: Methodology and Case Studymentioning

confidence: 93%

A probabilistic long‐term framework for site‐specific erosion analysis of wind turbine blades: A case study of 31 Dutch sites

et al. 2021

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“…The droplet impact causes local pitting, progressive material loss and increases the local surface roughness of the leading edge, consequentially decreasing the overall aerodynamic efficiency [83][84][85][86][87]. The damage due to rain droplet impact can be found at several locations in blades, however most is found at the leading edge of the blade [60,78,88].…”

Section: Hydrometeors Collisionsmentioning

confidence: 99%

A review of impact loads on composite wind turbine blades: Impact threats and classification

Verma

Yan

et al. 2023

Renewable and Sustainable Energy Reviews

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“…Techniques for improving the erosion resistance of the leading edge are also discussed. Later on, Shankar Verma et al [38] showed that a significantly higher erosion damage rate is found for blades exposed to offshore rainfall conditions than for blades under onshore rainfall conditions. Law and Koutsos [39] investigated the energy losses associated with LEE on an operational wind farm, discovering that the average AEP is decreasing by 1.8% due to medium levels of erosion, with the worst affected turbine experiencing losses of 4.9%.…”

Section: Introductionmentioning

confidence: 99%

CFD Modeling of Wind Turbine Blades with Eroded Leading Edge

Carraro

Vanna

Zweiri

et al. 2022

Fluids

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The present work compares 2D and 3D CFD modeling of wind turbine blades to define reduced-order models of eroded leading edge arrangements. In particular, following an extensive validation campaign of the adopted numerical models, an initially qualitative comparison is carried out on the 2D and 3D flow fields by looking at turbulent kinetic energy color maps. Promising similarities push the analysis to consequent quantitative comparisons. Thus, the differences and shared points between pressure, friction coefficients, and polar diagrams of the 3D blade and the simplified eroded 2D setup are highlighted. The analysis revealed that the inviscid characteristics of the system (i.e., pressure field and lift coefficients) are precisely described by the reduced-order 2D setup. On the other hand, discrepancies in the wall friction and the drag coefficients are systematically observed with the 2D model consistently underestimating the drag contribution by around 17% and triggering flow separation over different streamwise locations. Nevertheless, the proposed 2D model is very accurate in dealing with the more significant aerodynamics performance of the blade and 30 times faster than the 3D assessment in providing the same information. Therefore the proposed 2D CFD setup is of fundamental importance for use in a digital twin of any physical wind turbine with the aim of carefully and accurately planning maintenance, also accounting for leading edge erosion.

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Effects of Onshore and Offshore Environmental Parameters on the Leading Edge Erosion of Wind Turbine Blades: A Comparative Study

Cited by 8 publications

References 31 publications

A probabilistic long‐term framework for site‐specific erosion analysis of wind turbine blades: A case study of 31 Dutch sites

A probabilistic long‐term framework for site‐specific erosion analysis of wind turbine blades: A case study of 31 Dutch sites

A review of impact loads on composite wind turbine blades: Impact threats and classification

CFD Modeling of Wind Turbine Blades with Eroded Leading Edge

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