Estimating Air Density Using Observations and Re-Analysis Outputs for Wind Energy Purposes

Floors, Rogier; Nielsen, Morten

doi:10.3390/en12112038

Cited by 21 publications

(15 citation statements)

References 12 publications

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“…Given the great hub heights of modern turbines, these mesoscale models are interesting, because they give a good approximation of wind speed at these heights when vertical interpolation from the original η model levels is used. Anyway, Floors et al [37] have shown that air density should be also corrected. For instance, an air density reduction of 2% is expected according to their model for a turbine with a tower of 200 m. Therefore, in future studies about seasonal variations of air density this aspect of the hub height and the consequent reduction of air density should be introduced.…”

Section: Discussionmentioning

confidence: 99%

“…In another recent work, Floors et al [37] mentioned the importance of air density in wind energy potential estimation, but in their case the subject consists in the reduction of air density at the hub height compared to air density obtained from measurements at lower levels. Additionally, they have found that using re-analysis data (ERA5 in their case) to estimate air density gives similar or smaller errors compared to using nearest measurements around the point of study.…”

Section: 2mentioning

confidence: 99%

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Seasonal Correction of Offshore Wind Energy Potential due to Air Density: Case of the Iberian Peninsula

et al. 2019

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A constant value of air density based on its annual average value at a given location is commonly used for the computation of the annual energy production in wind industry. Thus, the correction required in the estimation of daily, monthly or seasonal wind energy production, due to the use of air density, is ordinarily omitted in existing literature. The general method, based on the implementation of the wind speed’s Weibull distribution over the power curve of the turbine, omits it if the power curve is not corrected according to the air density of the site. In this study, the seasonal variation of air density was shown to be highly relevant for the computation of offshore wind energy potential around the Iberian Peninsula. If the temperature, pressure, and moisture are taken into account, the wind power density and turbine capacity factor corrections derived from these variations are also significant. In order to demonstrate this, the advanced Weather Research and Forecasting mesoscale Model (WRF) using data assimilation was executed in the study area to obtain a spatial representation of these corrections. According to the results, the wind power density, estimated by taking into account the air density correction, exhibits a difference of 8% between summer and winter, compared with that estimated without the density correction. This implies that seasonal capacity factor estimation corrections of up to 1% in percentage points are necessary for wind turbines mainly for summer and winter, due to air density changes.

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Section: Discussionmentioning

confidence: 99%

Section: 2mentioning

confidence: 99%

Seasonal Correction of Offshore Wind Energy Potential due to Air Density: Case of the Iberian Peninsula

et al. 2019

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“…ERA5 provides pressure, temperature and humidity at sea level which allows calculation of local air density. Most wind farm feasibility studies ignore the impact that air density changes have on wind energy production [9,10]. Instead, a constant value around 1.225 kg/m 3 (ρ 0 ) is assumed at sea level while at higher altitudes, their yearly averages are used.…”

Section: Introductionmentioning

confidence: 99%

The Consequences of Air Density Variations over Northeastern Scotland for Offshore Wind Energy Potential

et al. 2019

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Hywind-Scotland is a wind farm in Scotland that for many reasons is at the leading edge of technology and is located at a paradigmatic study area for offshore wind energy assessment. The objective of this paper is to compute the Capacity Factor ( C F ) changes and instantaneous power generation changes due to seasonal and hourly fluctuations in air density. For that reason, the novel ERA5 reanalysis is used as a source of temperature, pressure, and wind speed data. Seasonal results for winter show that C F values increase by 3% due to low temperatures and denser air, with economical profit consequences of tens of thousands (US$). Hourly results show variations of 7% in air density and of 26% in power generation via FAST simulations, emphasizing the need to include air density in short-term wind energy studying.

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“…In recent publications [13,32,33], the authors developed a technique to seasonally estimate the influence of instantaneous air density changes on the capacity factor of a given turbine. Floors et al [34] emphasized, like us, the importance of air density, and also used ERA5 to study its effects. In this sense, the main physical magnitude that synthesizes the influence of wind speed with air density is the wind power density, the main parameter used for map representation of offshore wind energy in this work for Lebanon.…”

Section: Introductionmentioning

confidence: 93%

Evaluation of Lebanon’s Offshore-Wind-Energy Potential

Ibarra-Berastegi

Ulazia

Sáenz

et al. 2019

JMSE

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The only regional evaluation of Lebanese wind-energy potential (National Wind Atlas) dates back to 2011 and was carried out by a United Nations agency. In this work, data from the most recent reanalysis (ERA5) developed at the European Center for Medium Range Weather Forecast (ECMWF), corresponding to the 2010–2017 period, were used to evaluate Lebanese offshore-wind-energy potential. In the present study, wind power density associated to a SIEMENS 154/6 turbine was calculated with a horizontal resolution of 31 km and 1 hour time steps. This work incorporated the impact of air density changes into the calculations due to the seasonal evolution of pressure, temperature, and humidity. Observed average offshore air density ρ 0 was 1.19 kg / m 3 for the 2010–2017 period, but if instead of ρ 0 , hourly ρ values were used, seasonal oscillations of wind power density ( W P D ) represented differences in percentage terms ranging from −4% in summer to +3% in winter. ERA5 provides hourly wind, temperature, pressure, and dew-point temperature values that allowed us to calculate the hourly evolution of air density during this period and could also be used to accurately evaluate wind power density off the Lebanese coast. There was a significant gradient in wind power density along the shore, with the northern coastal area exhibiting the highest potential and reaching winter values of around 400 W / m 2 . Finally, this study suggests that the initial results provided by the National Wind Atlas overestimated the true offshore-wind-energy potential, thus highlighting the suitability of ERA5 as an accurate tool for similar tasks globally.

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Estimating Air Density Using Observations and Re-Analysis Outputs for Wind Energy Purposes

Cited by 21 publications

References 12 publications

Seasonal Correction of Offshore Wind Energy Potential due to Air Density: Case of the Iberian Peninsula

Seasonal Correction of Offshore Wind Energy Potential due to Air Density: Case of the Iberian Peninsula

The Consequences of Air Density Variations over Northeastern Scotland for Offshore Wind Energy Potential

Evaluation of Lebanon’s Offshore-Wind-Energy Potential

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