Wind speed measurements and predictions over Belmont Hill, Wellington, New Zealand

Flay, Richard G.J.; King, Andrew; Revell, Michael J.; Carpenter, Paul J.; Turner, Richard; Cenek, P D; Pirooz, Amir Ali Safaei

doi:10.1016/j.jweia.2019.104018

Cited by 23 publications

(9 citation statements)

References 29 publications

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“…WAsP is a well-established industrial standard as a computer-based program and has been created by the Department of Wind Energy at the Danish Technical University in 1987 [44]. It is a widely used tool for projects related to wind energy and wind engineering [26] in wind resource evaluation, energy yield calculations, and site selection of a wind energy facility.…”

Section: Wind Atlas Analysis and Application Programmentioning

confidence: 99%

“…Ko and Jeong [25] used statistical models such as Weibull and Rayleigh distributions to determine the annual energy density, annual energy production (AEP), and capacity factor in Weno Island, Chuuk State, and Micronesia. Flay and King [26] applied CFD, Wind Atlas Analysis and Application Program (WAsP) models, and wind-tunnel testing in New Zealand's installed infrastructure to improve wind speed forecasting methods for the wind pattern over complex terrain. Rogers and Ashtine [27] determined the maximum potential installed wind capacity in the Caribbean Island of Barbados.…”

Section: Introductionmentioning

confidence: 99%

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Wind Farm Site Selection Using WAsP Tool for Application in the Tropical Region

et al. 2021

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Wind energy is one of the most promising renewable energy technologies worldwide; however, assessing potential sites for wind energy exploitation is a challenging task. This study presents a site suitability analysis to develop a small–scale wind farm in south–eastern Thailand. To this aim, the most recent available data from 2017 to 2019, recorded near the surface, at nine weather stations of the Thai Meteorological Department (TMD) were acquired. The analysis was conducted using standard wind–industry software WAsP. It was found that the mountain peaks and ridges are highly suitable for small–scale wind farm development. Nevertheless, the wind data analysis indicates that regions fall in low–to–moderate wind classes. The selected sites in south–eastern Thailand have mean wind speeds ranging from 5.1 m/s to 9.4 m/s. Moreover, annual energy production (AEP) of 102 MWh to 311 MWh could be generated using an Enercon E–18 wind turbine with a rated power of 80-kW at the hub height of 28.5 m. The Levelized Cost of Energy (LCOE) reveals that the development cost of a small–scale wind farm is lowest in the Songkhla and Yala provinces of Thailand, therefore these two locations from the investigated study region are financially most suitable. The findings could encourage researchers to further investigate low–speed wind energy mechanisms in tropical regions, and the demonstrated approach could be reused for other regions.

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Section: Wind Atlas Analysis and Application Programmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Wind Farm Site Selection Using WAsP Tool for Application in the Tropical Region

et al. 2021

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“…In recent years, CFD simulation has become a popular research method for studying airflow characteristics (Kataoka et al, 2020). Based on field measurements and wind-tunnel modelling, Flay et al (2019) used large eddy simulation (LES) to analyze the wind flow over the natural complex terrain of Belmont Hill, and demonstrated that the numerical simulations can closely match the measured results. Li et al (2016) simulated the wind field characteristics around bridge sites with complex terrain in the southwestern mountainous areas of China, and discussed the blocking effect of mountains on airflow.…”

Section: Introductionmentioning

confidence: 99%

“…To study the characteristics of the wind field in the atmospheric boundary layer, many scholars at home and abroad have carried out related research by means of field measurements (Xie et al, 2022; Xue, 2022), wind tunnel tests (Flay et al, 2019), and numerical simulations (Li et al, 2016). Field measurement is a direct and effective method for monitoring the actual wind field.…”

Section: Introductionmentioning

confidence: 99%

CFD Simulation of Wind Field Characteristics in Mining Areas: A Case Study of the Xinxing Coal Mine in Wuhai City, Inner Mongolia, China

Haoran,

Jingxue,

Tingning

et al. 2023

Journal of Resources and Ecology

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The large amount of coal mining activity in the arid region of northwestern China leads to vegetation degradation and a greater probability of strong winds. The characteristics of windy fields directly affect the sand-dust transportation process. To capture the wind field characteristics in a mining area, numerical simulation of computational fluid dynamics (CFD) was conducted using the Reynolds-Averaged Naiver-Stokes (RANS) turbulence model based on open source software OpenFOAM，taking Xinxing Coal Mine in Wuhai, Inner Mongolia, China as an example. The field test results at several observation points in the mining area were adopted for validating the numerical results. The distributions of mean wind speed and turbulence kinetic energy in the mining area for the W, NW and E wind directions are discussed. The results show that the mean wind speed distributions of the mining area are greatly affected by the raised mountains or hills on the eastern and western sides. When the approaching wind comes from the W and E directions, the mean wind speed is relatively low behind the raised terrain due to the wake effect. However, the magnitude of turbulent kinetic energy shows a relatively large value. The wake effect of mountains or hills is less pronounced as the approaching wind comes from the NW direction. The reduced mean wind speed and increased turbulence kinetic energy are also observed near the low-lying pits in the mining area. The results of this study can provide a theoretical basis for the prevention and control of aeolian sand and its construction in mining areas.

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“…The results show that the precision of the LES model is relatively higher, and the simulation effect of the windward side is better than that of the leeward side. For the acceleration effect, which is the concern of most structural designers, Flay et al [8] (2019) discussed the wind speed ratio of nine measuring points at Belmont Hill in New Zealand through the WTT with a scale of 1:2000, full-scale numerical simulation, and field measurement. The results also show that the consistency between WTT and field measurement is better than that of CFD.…”

Section: Introductionmentioning

confidence: 99%

Correction of Field-Measured Wind Speed Affected by Deterministic Interference Factors

et al. 2022

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The observations of meteorological wind speed may be biased due to the influence of various distractions. Therefore, the original measured data should be corrected in a targeted manner. Wind tunnel tests (WTT) and computational fluid dynamics (CFD) numerical simulation methods are used to study the local wind environment characteristics of observation sites in Noi Ling Ding Island (NLDI) and Ping An International Financial Center (PAFC) in the Shenzhen area. The interference effects of NLDI and the building components and instruments in the hollow-layer atop PAFC on their corresponding anemometer measurement results were analyzed, and a quantitative description was provided with the wind speed influence coefficient (CVI), which is the wind speed ratio in disturbed and undisturbed cases. Results show that the CVI of WTT at the NLDI site is slightly higher than that of CFD, and the wind speed in the wind-sensitive direction is accelerated by 12% due to the influence of NLDI. The large pillars at the corner of PAFC have a considerable occlusion effect on the wind speed under the wind direction of 45°. An acceleration effect with CVI of 1.163 is found in the dominant wind direction when instruments are absent atop the hollow-layer, whereas a sheltering effect is observed with the CVI of 0.593 when instruments are present. These results are used to correct the recorded wind speed at the NLDI and PAFC sites during Super Typhoon Manghut with No. 201822, and then converted into the 10 min mean wind pressure value at 10 m height under the standard landform. The reference wind pressure values obtained are 0.526 and 0.505 kPa. The analogous conversion values achieve the purpose of mutual verification, and the effectiveness and reliability of the methodologies are presented.

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Wind speed measurements and predictions over Belmont Hill, Wellington, New Zealand

Cited by 23 publications

References 29 publications

Wind Farm Site Selection Using WAsP Tool for Application in the Tropical Region

Wind Farm Site Selection Using WAsP Tool for Application in the Tropical Region

CFD Simulation of Wind Field Characteristics in Mining Areas: A Case Study of the Xinxing Coal Mine in Wuhai City, Inner Mongolia, China

Correction of Field-Measured Wind Speed Affected by Deterministic Interference Factors

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