Wind Power Potential in Interior Alaska from a  Micrometeorological Perspective

Ross, Hannah; Cooney, John; Hinzman, Megan; Smock, Samuel; Sellhorst, Gary; Dlugi, R.; Mölders, Nicole; Kramm, Gerhard

doi:10.4236/acs.2014.41013

Cited by 4 publications

(12 citation statements)

References 70 publications

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“…Obviously, Equation 1does not explicitly depend on thermal stratification. As pointed out by [8], the vertical wind-profile function shows such a dependency. Being located in a steep valley (Figure 1), inversions frequently occur at Juneau.…”

mentioning

confidence: 74%

“…We applied the method by [8] to calculate the power and capacity factors for the seven tourist seasons and eight turbine types. Our study revealed that interannual variability in wind speed at hub height can cause differences in produced power that are of the order of the differences among turbine types with similar hub height.…”

Section: Discussionmentioning

confidence: 99%

“…The wind potential was assessed using the method outlined by [8]. Two-parameter Weibull distributions were fitted to the cumulative historgrams of each tourist season.…”

Section: Analysis Methodsmentioning

confidence: 99%

“…Since the energy is needed for cold ironing, we performed the investigation over the length of a cruise-ship season (May 15 to September 15). To achieve our goal, we used hourly output of simulated wind speeds for the tourist seasons of 2006 to 2012 [2] at hub height for eight different turbine types and applied the method described by [8] to assess potential power and capacity factors. The assessment used model-predicted wind speeds for two reasons: First, wind-speed observations rarely exist in tourism communities.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Uncertainty of Wind Power Usage in Complex Terrain—A Case Study

Mölders¹,

Khordakova²,

Gende³

et al. 2015

ACS

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This study investigated the uncertainty assessing wind-power production in valleys of complex terrain using Juneau, Alaska as the testbed. The wind-speed data stem from evaluated WRF/Chem simulations for seven tourist seasons (May 15 to September 15). The percentage of wind speeds between cut-in and cutout speed differed up to about 11% among tourist seasons and up to 15% among the examined wind-turbine types. The wind-speed probability density varied the strongest among tourist seasons for wind speeds less than 3 m•s −1 (6 m•s −1) for wind turbines with hub heights of about 80 m (30 m). At these heights, the interannual differences in the probability density of wind speeds at the rated or higher power were about half or less than those at wind speeds below 3 m•s −1 (6 m•s −1). The predicted average power output notably differed among tourist seasons. The tall (small) turbines had their highest predicted average production in 2006 (2012). The ranking among wind turbines regarding the predicted average power production was independent of the interannual variability in average power production. Capacity factors differed about 8% (6%) for the tall (small) tubines among tourist seasons. Within the same tourist season, capacity factors differed about 8% (5%) among turbine types. Estimates of capacity and potential power derived from 10 m wind-speed observations by an empirical formula commonly used to estimate wind speeds at hub height, differed up to 40% for 80 m height for some turbine types. Determinating the exponent of the empirical equation by means of WRF/Chem data showed that the traditional empirical approach failed in complex terrain.

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mentioning

confidence: 74%

Section: Discussionmentioning

confidence: 99%

“…The wind potential was assessed using the method outlined by [8]. Two-parameter Weibull distributions were fitted to the cumulative historgrams of each tourist season.…”

Section: Analysis Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Uncertainty of Wind Power Usage in Complex Terrain—A Case Study

Mölders¹,

Khordakova²,

Gende³

et al. 2015

ACS

Self Cite

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“…Here, we consider a natural coordinate frame with the unit vectors s t , s n , and s b that form a righthanded rectangular coordinate system at any given point of a curve in space (moving trihedron) like a trajectory or a streamline (see Figure 3), where the subscript s characterizes the streamline-related quantities. The velocity vector at a given point along the streamline is given by [56]). Even though air density is considered as spatially constant, Bernoulli's equation can often be applied to atmospheric flows.…”

Section: The Bernoulli Equationmentioning

confidence: 99%

On the Maximum of Wind Power Efficiency

Kramm¹,

Sellhorst²,

Ross³

et al. 2016

JPEE

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In our paper we demonstrate that the filtration equation used by Gorban' et al. for determining the maximum efficiency of plane propellers of about 30 percent for free fluids plays no role in describing the flows in the atmospheric boundary layer (ABL) because the ABL is mainly governed by turbulent motions. We also demonstrate that the stream tube model customarily applied to derive the Rankine-Froude theorem must be corrected in the sense of Glauert to provide an appropriate value for the axial velocity at the rotor area. Including this correction leads to the Betz-Joukowsky limit, the maximum efficiency of 59.3 percent. Thus, Gorban' et al.'s 30% value may be valid in water, but it has to be discarded for the atmosphere. We also show that Joukowsky's constant circulation model leads to values of the maximum efficiency which are higher than the Betz-Jowkowsky limit if the tip speed ratio is very low. Some of these values, however, have to be rejected for physical reasons. Based on Glauert's optimum actuator disk, and the results of the blade-element analysis by Okulov and Sørensen we also illustrate that the maximum efficiency of propellertype wind turbines depends on tip-speed ratio and the number of blades.

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Sustainability of Wind Energy under Changing Wind Regimes—A Case Study

Mölders¹,

Khordakova²,

Dlugi³

et al. 2016

ACS

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A method was introduced to assess the sustainability of energy production over the lifetime (~20 y) of wind turbines. Community Earth System Model simulations were downscaled for the tourist seasons (mid-May to mid-September) of 2006 to 2012 (CESM-P1) and 2026 to 2032 (CESM-P2) to obtain a reference and projected wind-speed climatology, respectively. The wind speeds served to calculate the potential power output and capacity factors of seven turbine types. CESM-P1 windspeed climatology, power output, and capacity factors were compared to those derived from wind speeds obtained by numerical weather forecasts for reference to known standard to wind-farm managers. Juneau, Alaska served as a virtual testbed as this region is known to experience changes in wind speeds in response to the Pacific Decadal Oscillation. CESM-P2 suggested about 2% decrease for wind speeds between the speeds at cut-in and rated power, and about 8%-10% decrease in potential wind-power output. This means that in regions of decadal climate variations, the sustainability of wind-energy production should be part of the decision-making process. The study demonstrated that using mean values of wind-speeds can provide qualitative knowledge about decreases/increases in potential energy production, but not about the magnitude. Using the total individual wind-speed data of all seasons provided the same amount of total power output than summing up the power outputs of individual seasons. The main advantage of calculating individual seasonal wind-power outputs, however, is that it theoretically permits assessment of interannual variability in power output and capacity factors. Comparison to a known standard may help stakeholders in understanding of uncertainty and interpretation of projected changes.

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Wind Power Potential in Interior Alaska from a Micrometeorological Perspective

Abstract: ABSTRACT

Cited by 4 publications

References 70 publications

Uncertainty of Wind Power Usage in Complex Terrain—A Case Study

Uncertainty of Wind Power Usage in Complex Terrain—A Case Study

On the Maximum of Wind Power Efficiency

Sustainability of Wind Energy under Changing Wind Regimes—A Case Study

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