1) The document describes a wind analysis study conducted for a proposed wind turbine project on Poor Mountain in Roanoke County, Virginia. 2) It notes that publicly available wind data with a large 650 foot pixel size is not sensitive enough to local conditions and a poor basis for assessing environmental and economic impacts. Local data collection is recommended. 3) Charts and diagrams show wind patterns in the region, with higher wind speeds found in other nearby locations compared to the proposed Poor Mountain site.

1. Slide In response to the
1 need to clearly conduct
Creating a venue for a an objective,
Wind Analysis Study for a site on scientifically based,
Poor Mountain in Roanoke County, Virginia
COST/Benefit Analysis;
I have described as
accurately (to scale) as
possible within the
graphic venue and with
an ethical standard
based upon the best
interests of the human
and other species of
being on our planet.
Slide Clearly, the publicly
2 available data created
This image describes a 650 ft x 650 ft pixel size with a “computer‐
overlay of a Wind Density Analysis extrapolated
from data from sites, nationwide, on a vertical screen” pixel sized
elevation above sea level basis to assess electrical
energy production for a site on Poor Mountain in
(650’ x650’) conclusion
Roanoke County, VA seems to be
extraordinarily
insensitive to local
conditions and a poor
basis for weighing
benefit and
environmental loss.
The AWEA, an industry
organization and
AWS/Truepower, a
private engineering
consulting firm, both
advise that local data
be gathered to more
accurately describe the
energy production
potential of the siting.

2. Slide The yellow ring begins
Understanding the
3 Wind Developer’s to focus on a specific
Wind Analysis Study area of a proposed 18 –
for a site on
Poor Mountain in 2.5MW Turbine
Roanoke County, Plantation. Note that
Virginia
there are an
abundance of Class 5, 6
& & wind areas in the
Roanoke & Franklin
County vicinities.
Notably along the Blue
Ridge Parkway,
Mason’s Knob and
Cahas Mountain near
Boone’s Mill to the
east.
Slide As we begin to focus in
Understanding the
4 Wind Developer’s on the project site we
Wind Analysis Study see that the Wind
for a site on
Poor Mountain in Classes are
Roanoke County, predominately Class 3
Virginia
& Class 4 areas.
Notably, these are of
lower energy
producing potential
than many other Class
5, 6 & 7 wind areas in
the vicinity.

3. Slide With less than
5 desirable siting, in wind
Is this site on
power terms, than
Poor Mountain in recommended by the
Roanoke County,
Virginia a key
American Wind Energy
to accessing Association (AWEA), an
additional energy
resources from the
industry supported
abundant wind power organization: “In
bands near a model
city in the southern general, sites with a
Appalachians? Wind Power Class
rating of 4 or higher
are now preferred for
large scale wind
plants.”
9 turbines proposed
in Class 3 areas
5 turbines proposed
in Class 4 areas
3 turbines proposed
in Class 5 areas
1 turbine proposed in
Class 6 area
Slide Off‐shore winds are
6 relatively smooth,
stable, and more
predictable in terms of
constant flow.
On‐shore winds vary
wildly in the vertical
direction as influenced
by objects including
Mountain wave schematic. The wind flows buildings, trees and
towards a mountain and produces a first
oscillation (A). A second wave occurs further terrain.
A: Sea breeze (occurs at daytime)
away and higher. The lenticular clouds form at
B: Land breeze (occurs at night)
the peak of the waves

4. Slide The characteristics of
7 the wind in
mountainous terrain
where wind‐flow
patterns are “choppy”
makes analysis of
energy production
potential extremely
critical as to specific
site data collection
location & height.
Wind Flow Visualization over Appalachian Mountain Terrain
Poor Mountain wind Reaping - Roanoke County - Virginia
Slide By definition, these
The wind profile power law relationship is:
8 u/ur = (z/zr)α algorithms are yielding
where u is the wind speed (in meters per second) at height z (in meters), and ur is the
known wind speed at a reference height zr. The exponent (α) is an empirically derived
“quite erroneous”
coefficient that varies dependent upon the stability of the atmosphere. For neutral
stability conditions, α is approximately 1/7, or 0.143.
estimates. The
In order to estimate the wind speed at a certain height x, the relationship would be
rearranged to:
roughness factor
ux = ur(zx/zr)α
The value of 1/7 for α is commonly assumed to be constant in wind resource
clearly requires much
assessments, because the differences between the two levels are not usually so great
as to introduce substantial errors into the estimates (usually < 50 m). However, when
more locally based
a constant exponent is used, it does not account for the roughness of the surface, the
displacement of calm winds from the surface due to the presence of obstacles (i.e.,
evaluation. Terrain
zero‐plane displacement), or the stability of the atmosphere. In places where trees or
structures impede the near‐surface wind, the use of a constant 1/7 exponent may
based factors for
yield quite erroneous estimates, and the log wind profile is preferred. Even under
neutral stability conditions, an exponent of 0.11 is more appropriate over open water
“wind‐turbulence”
(e.g., for offshore wind farms), than 0.143, which is more applicable over open land
surfaces. impact in mountain
terrain is not
addressed, thereby,
making data
extrapolation less
reliable. Wind shear,
the radical shifts in
wind flow are most
common in the
mountains. The wind
characteristics that
attract migrating
species, thermals and
downdrafts along
ridges create a
“roughness” factor on
an extreme ratio of
difference as described
here that it become

5. apparent that site
specific data and
analysis must be
undertaken in
mountainous terrain.
Slide This equation
9 Rayleigh Distribution ‐ Wind Speed estimates theoretical
The purpose of this page is to illustrate the use of the Rayleigh distribution to estimate the
energy recovered by a medium sized wind turbine. The parameters are illustrative and it is energy conversion from
important to obtain site specific parameters for a project evaluation. wind to electricity.
Basic Equation
The equation for energy recovery from the wind is as follows:
Slide Coefficient of Performance For the preceding
10 Not all the energy can be recovered from a Raleigh Distribution
wind stream. The theoretical maximum value
for the coefficient of performance is 0.593. An formula, the coefficient
"ideal" wind turbine with this maximum value of performance factor
is known as a Rayleigh‐Betz machine.
In practice the value of the maximum values of
used is between the
coefficient is in the range 0.25 to 0.45. 25% to 45% range. This
In general, the larger the machine the higher
the value. Also the use of variable pitch rotors
number should not b e
can optimize the coefficient of performance confused with the
for a range of wind speeds. The curve used in
the example is shown below.
“capacity factor”, which
The maximum value of the coefficient has addresses performance
been set close to the modal wind speed for
Rayleigh averages in the range 5 ‐ 7 m/sec. The
over periods of time
rotor design should be optimized for the site. (typically annual).

6. Slide A Capacity Factor is
11 number that is
applied to identify
the “on site”
productivity of the
turbine or installation
of turbines. The
number is expressed
as a ratio of energy
produced (over time)
divided by the “Name
From GE Wind (2.5xl Power curve speculation NOT from GE)
Plate Capacity” (over
the same amount of
time).
Invenergy, LLC
provided a “35%
capacity factor” to Dr.
Sean McGinnis, dean
of the Department of
Green Engineering at
Virginia Tech. which
he used to establish
projections of
providing electrical
needs to 10,000
Roanoke Valley
Homes annually. He
also postulated that
98,000 tons of CO2
emissions would be
curtailed as a result
of using the 35%
capacity factor.
To achieve this
measure of efficiency,
the wind must
operate these
turbines on Poor
Mountain at a
constant speed of

7. 6.75 m/s (15.1 mph),
24 hours per day, 365
days per year. This
alone makes claims
of producing
electricity needs for
10,000 homes (at an
AEP rate of 14,400
KWH/home in
Roanoke)
exaggerated by over
500%!!!
Slide On Bent Mountain, we
12 are blessed with a
population of diverse
interest and expertise.
Our interests,
education & expertise
have shaped us into a
community family that
understands how to
appreciate and live
with our natural
environment.
We have a registered
private weather station
on the Bent Mountain
plateau the has been
compiling 5‐minute
data for six years. The
exact location of the
station will be kept
private with for the
sake of the owner, with
the exception that is in
an equal or greater
wind classification area
than the proposed
turbine locations.

8. A close friend, with
electrical engineering
degree & independent
streak recently emailed
this about a data from
a local Bent Mountain
Weather station:
"Based on his wind
data there was no day
in July or Aug (2010)
that the turbines would
have run for more than
5 minutes on any one
day.
The total (for 18
turbines) in July was
101 minutes to
produce 5586 KwHr /
turbine
The total (for 18
turbines) in Aug was
105 minutes to
produce 1942 KwHr /
turbine
Since both are almost
certainly less than the
control circuits draw
from the grid. CC folks
must live without A/C,
refigeration"

9. Slide Please look closely at
13 Poor Mountain Preserve
this image. It clearly
Bottom Creek
The Nature Conservancy
Globally Rare Pirate‐bush conveys visual
Headwaters
evidence of a large
undisturbed oxygen
Big Laurel Creek
Headwaters
producing, life
sustaining areas of
natural environment.
Thirty years ago,
Roanoke County
Bottom Creek Gorge
Preserve identified the hollow
The Nature Conservancy
EPA/DEQ Tier III Stream
behind my home as a
prospective site for a
landfill, because it was
remote from the
density of population
in the valley. Thirty
years later, we still
think that “for the
greater good(?)” and
the “financial benefit
of a few”, the
unspoiled natural
environment that we
have left in the area is
easily sacrificed for our
ever‐growing energy
demands.