TITLE:
Wind Power Potential in Interior Alaska from a Micrometeorological Perspective
AUTHORS:
Hannah K. Ross, John Cooney, Megan Hinzman, Samuel Smock, Gary Sellhorst, Ralph Dlugi, Nicole Mölders, Gerhard Kramm
KEYWORDS:
Wind Power; Power Efficiency; Wind Power Potential; Wind Power Prediction; WRF/Chem; Micrometeorology; Momentum Theory; Blade Element Analysis; Betz Limit; Glauert’s Optimum Rotor; Balance Equation for Momentum; Equation of Continuity; Balance Equation for Kinetic Energy; Reynolds’ Average; Hesselberg’s Average; Bernoulli’s Equation; Integral Equations; Weibull Distribution; General Logistic Function; Eva Creek Wind Farm
JOURNAL NAME:
Atmospheric and Climate Sciences,
Vol.4 No.1,
January
15,
2014
ABSTRACT:
The wind power
potential in Interior Alaska is evaluated from a micrometeorological
perspective. Based on the local balance equation of momentum and the equation
of continuity we derive the local balance equation of kinetic energy for
macroscopic and turbulent systems, and in a further step, Bernoulli’s equation
and integral equations that customarily serve as the key equations in momentum
theory and blade-element analysis, where the Lanchester-Betz-Joukowsky limit,
Glauert’s optimum actuator disk, and the results of the blade-element analysis
by Okulov and Sorensen are exemplarily illustrated. The wind power potential at
three different sites in Interior Alaska (Delta Junction, Eva Creek, and Poker
Flat) is assessed by considering the results of wind field predictions for the
winter period from October
1, 2008, to April 1, 2009 provided by the Weather Research and Forecasting
(WRF) model to avoid time-consuming and expensive tall-tower observations in
Interior Alaska which is characterized by a relatively low degree of
infrastructure outside of the city of Fairbanks. To predict the average power
output we use the Weibull distributions derived from the predicted wind fields
for these three different sites and the power curves of five different
propeller-type wind turbines with rated powers ranging from 2 MW to 2.5 MW.
These power curves are represented by general logistic functions. The predicted
power capacity for the Eva Creek site is compared with that of the Eva Creek
wind farm established in 2012. The results of our predictions for the winter
period 2008/2009 are nearly 20 percent lower than those of the Eva Creek wind
farm for the period from January
to September 2013.