Energy Production
Potential of Wind Resources in Texas
By: Todd J. Schram
CE394.K3: GIS in Water Resources
Fall 1998 Term Project
December 4, 1998
Outline
Presentation Slides
Background
The development of renewable energy
resources gained major attention over two decades ago during the energy crisis
that occurred in the United States. However after the crisis subsided, the
importance placed on renewable energy resources withered and it's research
disappeared. Recently, the development of renewable energy facilities has been
projected to experience rapid growth. In particular, wind energy was sited in a
recent journal article as 'the world's fastest growing energy resource' (Solar
Today, March 1998). The wind energy industry has predicted a 50% increase in
wind energy capacity in the U.S. over the next two years. In Texas, there are
two wind farms scheduled for project completion by the end of this year, a 34.8
MW wind farm in Big Spring and 4.5 MW wind farm in Lubbock.
The projected growth may be attributed to the electric utility deregulation
that is occurring in the U.S. and has created a restructured electricity market
with new demands. Consumer choice of electricity companies provides an impetus
for product differentiation. In the quest for product differentiation, companies
have resorted to the marketing of the source of the energy since electricity,
the final product, is the same. This trend can be seen in states where the
initial steps of deregulation have already taken place. In an attempt to seek
nitch markets, a number of companies have taken a green energy approach
and been developing less-polluting and renewable energy resources.
Advertised percentages of green energy are utilized to attract the
marketing segment defined as environmentally-conscious consumer. In this
changing industry, wind energy resources show much promise in certain areas of
the country in supplying the new demands anticipated.
This project will not look at evaluations required for siting wind farms, but
be directed towards informing the consumer on the potential of wind resources.
Additionally, the continuing project will incorporate a computer program for
energy evaluation of domestic applications of wind turbines.
Objective
The goals of the analysis are to develop
a state-wide grid maps of wind resources for the state of Texas based on surface
wind speed data. The grid maps will contain the mean surface wind speeds
for seasonal and annual time periods. Methods to modify the mean surface wind
speed maps will be developed to account for the variations in wind speed with
turbine height above ground. Utilizing the annual modified wind speed grid map,
a method will be developed to calculate the potential energy production from a
single wind turbine. An example energy evaluation for a domestic
application will be run to simulate the method. A program developed using MS
Visual Basic will allow the program user to query the energy production for
selected location, turbine, and economic parameters. The overall goal of this
continuing project is to develop the program to interact with ArcView and report
the results of an energy evaluation based on data queried from ArcView.
Sources of Data
All data collected
for this project were retrieved through various internet sites as referenced
below.
Graphic Data
The geographic limit of the project is the state of Texas,
therefore the following base maps were retrieved from the Texas Natural
Resources Information System website ( http://www.tnris.state.tx.us/ ).
| File Description |
Filename |
| Cities |
cities.e00 |
| Counties |
tx250k.e00 |
| State Boundary |
txborder.e00 |
The original format of the
downloaded files are gzipped and require a zip utility to extract the Arc/Info
export files (*.e00). These exports files are added to ArcView after
importing the export files using the Import71 program available under the ESRI
directory. The files are projected in Texas State Mapping
System format.
Through the Environmental Protection Agency (EPA) ftp site
(ftp://ftp.epa.gov:/pub/EPAGIRAS/), Land Use/Land Cover files are accessed. The
downloaded files are gzipped Arc/Info export files. The projection parameters of
the files are:
| Type |
Albers Conical Equal Area |
| Spheroid |
Clarke 1866 |
| Central Meridan |
-96 00 00 |
| Reference Latitude |
23 00 00 |
| Standard Parallel |
29 30 00 |
| False Northing |
0.0 |
| False Easting |
0.0 |
From the data files
provided by ESRI with their ArcView software package, the zip codes for the U.S.
were used. The projection of the file is geographic coordinates.
Raw Data
The mean surface wind speed data was downloaded from the VEMAP-
Vegetation\Ecosystem Modeling and Analysis Project website (http://neit.cgd.ucar.edu/vemap/. The
datasets are grid-averaged surface wind speeds normalized at a 10 meter height.
Datasets exist for seasonal three-month and annual averages. The data cover the
entire conterminous U.S. in 0.5o x 0.5o grid cells. The
data cells are scaled up by a factor of 10. The grid cells are referenced using
the latitude and longitude of the cell center. For grid cells with areas that
are more than half covered by water, the cell is assigned a no data value of
-9999.
| File Description |
Filename |
| Annual |
w.ann |
| Winter (Jan. - Mar.) |
w.jan |
| Spring (Apr.-Jun.) |
w.apr |
| Summer (Jul.- Sep.) |
w.jul |
| Fall (Oct. - Dec.) |
w.oct |
Turbine Data
As part of the project, an evaluation of the energy
production for a small wind turbine was completed. The parameters for the
evaluation were developed using data provided by Bergey Windpower Corporation
(http://www.bergey.com/) for the turbine model BWC1500. A 120V VCS-1.5
voltage regulator and guyed lattice tower were selected for purposes of the
economic evaluation. The parameters of the model BWC1500 are:
| Rated Power |
1500 W |
| Rotor Diameter |
3.0 m |
| Tower Height |
20 m |
| Estimated Investment Cost |
$8,000 |
Data Manipulation
The format of the
surface wind speed dataset was adjusted for ArcView usage. The format was
converted from the original ASCII Raster data to a database (*.dbf) file.
This conversion was completed using an Excel macro. ASCII Raster data are
tabular data with implicit latitude and longitude references based on the row
and column where the data are found. For the VEMAP wind speed data, the
row and column of data are related to the latitude and longitude by the
following equations:
row_number = 1 + [( 49.0 - site_latitude )/0.5]
column_number
= 1 + [(124.5 - site_longitude)/0.5]
An identifier for each grid
cell is numbered consecutively from 1 to 5520. This grid cell number is referred
to as the grid point and is based on the row and column number. It is
determined as follows:
grid point = [(row_number - 1) * 115] + column_number
To
extract the necessary data from the VEMAP datasets, the following geographic
extents of Texas were used:
- East: 93oW
- West: 107oW
- North: 37oN
- South: 26oN.
At this point, the format of the
database file created is: ROW, COLUMN, SPEED, GRIDPOINT.
Equations Used
Below are the equations needed
for the wind resource and energy evaluation.
Altitude Varying Wind Speed
Power Law Equation
Logarithmic Velocity Distribution Equation
Figure below shows the principle of the logarithmic velocity distribution.
Note y in figure corresponds to z in equation.
(Holley, E.R. and Rumer, R.R., Introduction to Environmental Fluid
Mechanics, unpublished, 1998)
Surface Roughness Assignment to
Anderson Land Use Codes
Wind Power
The evaluation of wind energy is dependent on analyzing the
wind speed for a given area. The total inherent energy of the wind is
determined by the following equation:
PTotal:
Total power (Watts)
r : Air density
(kg/m3)
A: Rotor Swept Area (m2)
u:
wind speed (m/s)
For this evaluation, the density of air was assumed
constant at 1.225 kg/m3.
The electrical power created from the available wind energy is determined
using the efficiencies of the mechanical-to-electrical energy conversion
equipment.
Poutput: Total Power Out (Watts)
noverall: overall efficiency
nblade: blade efficiency
ngearbox:
gearbox efficiency
ngenerator: generator efficiency
Simple Payback Period
SPB = [Capital Investment]/[Net Annual
Benefits]
Procedures
Wind Resource Maps
Using Arc/Info
Create Surface Wind Speed Grid
Arc/Info was first utilized to
develop a polygon grid that encompasses the limits of the wind speed data.
From the Arc: prompt of Arc/Info, the Generate command was initiated to form a
new coverage. From the Generate: prompt, the fishnet command was run to
develop a grid-like net of lines. The following parameters were used for the
fishnet command:
FISHNET Origin = -107,26
Y-axis Origin = -107,37
Cell Size
= 0.5, 0.5
Rows, Columns = 23,29
The second step of the process
is to invoke the Build command from the Arc: prompt on the coverage. Typing in
Build <coverage_name> poly creates polygon features from the fishnet
coverage produced. Each cell of the fishnet is created as a polygon, which
yields 667 polygons for the data extents.
Using ArcView
Combine Surface Wind Speed Data with Polygon-Grid Shape File
Open
ArcView project and use Add Theme to add the coverage created in Arc/Info.
Use Add Table to add the wind speed database file created in Excel. Since
a single value is needed to link the table to the attributes of the fishnet
theme, the grid cell number of the attribute table is used. This requires a
modification to the wind speed datasets. Using the attribute table, select
Table/Start Editing and add two fields: Row and Column. Now using the display of
the polygon theme, rows and columns of data can be highlighted to determine the
corresponding grid cell numbers. The row and column numbers can be added
manually using the wind dataset row and columns as a reference. Select
Table/Save Edits when all grid cells are assigned a row and column number. Using
Excel, access the attribute table and wind database files. The Data/Sort command
needs to be used first to sort the data so the same order of cells exist in both
files. Selecting sort first by row and second by column for both files
lines up the corresponding grid cells in the same order. From the attribute
table, select the columns corresponding to the grid cell number, row and column
and copy to the wind dataset files. Now both files have a common field which can
be accessed to join them. The attribute and data tables are combined using
Table/Join. The grid cell number fields that are used to relate the tables
should be highlighted and the attribute table window should have focus before
running Table/Join.
Now with wind speed data joined to the attribute table of the polygon theme,
the wind speed values can be assigned as the values of the polygons.
Theme/Legend Editor is invoked to set the legend type to graduated color and the
classification field to Speed. The result is a polygon-gridded wind speed theme
in geographic coordinates.
Project to Texas State Mapping System
Since the theme was created
using geographic latitude and longitude coordinates, the theme must be projected
in order to use with the base maps. The base maps used require it to be
projected to the Texas State Mapping System. Highlighting the Project window and
then File from the menu shows the item Extensions which allows the Projector!
extension to be added to ArcView. ArcView is capable of changing the
projections of views, but cannot alter the underlying datasets of the themes.
Therefore, this extension is needed to do complete projections that produce new
datasets of eastings and northings.
Selecting the View and then View/Properties, the Map Units should be changed
to decimal degrees. The Change Projection button (found at the far right of the
upper row of menu buttons) can now be run from the menu. Select meters for the
output units.
The Projection Properties dialog box appears and the following parameters
were set to change the projection into the Texas State Mapping System:
Type: Lambert Conformal Conic (Conterminous U.S.)
Select the
custom option button.
Spheroid: GRS80
Central Meridan: -100
Reference Latitude: 31.166667
Standard Parallel 1: 27.416667
Standard Parallel 2: 34.916667
False Northing: 1000000
False
Easting: 1000000
Select yes to recalculate the area, perimeter and length. Select a new view
into which the new projection should be placed.
Convert to a Grid Theme
A grid theme of the data is required in
order to perform the necessary calculations on the maps. With the theme of
the projected polygons active, select Theme/Convert to Grid. Insert the filename
of the new grid to be created. Select the Output Extents of Grid to be the
same as the extents of the theme it is created from. Set the cell value equal to
Speed. Select yes for joining the attributes table and adding the grid.
Highlight the new grid theme and select Theme/Edit Legend. Select the field to
be equal to Value.
Add State Boundary to Project
Using the Add Themes button select
the file for the state boundary to be added to the current view.
Clip Grid to State Boundary
To clip the grid the ArcView
extension CRWR-Raster must be activated. By selecting File/Extensions while the
project window is active, the CRWR-Raster extension can be checked on. From the
new menu heading for the extension, select CRWR-Raster/Clip by Polygon to run
the script. This script creates a new theme based on the active grid
theme. Select the trimming polygon to be the state boundary shape theme. A mean
surface wind speed grid clipped to the boundaries of Texas has now been
completed.
Mean Surface Wind Speed Grids
The previous steps are repeated for
all datasets of the mean surface wind speed. The annual and seasonal mean wind
speed grids developed are displayed below.
The legend for the maps shows
values in 0.1 m/s.
Legend
Annual
Winter
Spring
Summer
Fall
Wind Energy Map Calculations
Using the annual wind speed grid created
previously, map calculations in ArcView can be conducted to determine the
harnessable wind energy across the state. The calculation of wind energy
for a specific turbine from a wind speed grid can be divided into the following
steps:
- Modify wind speed grid for altitude adjustment,
- Calculate total wind power,
- Calculate electrical power generated by the turbine,
- Calculate annual electrical energy production,
- Calculate annual energy value, and
- Perform simple payback economic analysis.
All equations are
explained in the Methodology section of the report. Also, all calculations
stated below were performed using the Analysis/Map Calculator command.
Modify Wind Speed
The initial step modifies the surface wind
speed grid, designated here as [Wind Speed Grid], to determine an estimated wind
speed for an altitude different than the normalized height of 10 meters. The
height of the turbine is designated [Height]. The modified wind speed was
calculated using the Power Law equation discussed previously. Using the
following equation in map calculator, the modified wind speed grid was created:
[Wind Speed Grid].Value*([Height]/10)1/7
Calculate Total Wind Power
The modified wind speed grid,
designated [Mod Wind Speed Grid], is used to compute the total power of the wind
through a given area determined by the diameter of the turbine rotor. This area
is designated [Swept Area of Rotor]. The following equation in map calculator
was used to create the total wind power grid in units of watts:
([Mod Wind Speed Grid].Value/10)3*(1/2)*1.225*[Swept
Area of Rotor]
Note that the modified wind speed grid is divided by
10 to account for the scale factor of the data.
Calculate Electrical Power Generated
The wind power grid,
designated [Wind Power Grid], is used to compute the electrical power generated
for a single turbine. The electrical power is solely a function of the
efficiency, [Efficiency Overall]. The efficiencies used for the two runs of
parameters were 28% and 35%. The following equation in map calculator was used
to create the electrical power grid in units of watts:
[Wind Power Grid].Value*[Efficiency Overall]
Note that
the operation of a wind turbine requires that the wind speed be at least equal
to a minimum start-up value. This translates to periods of non-use when
conditions are not satisfactory, and therefore, implies that the electrical
power generation is overestimated.
Calculate Annual Energy Production
The electrical power grid,
designated [Electrical Power Grid], is used to compute the annual energy
production for a single turbine. The assumptions for production are continuous
wind turbine operation throughout the year. This is equivalent to 8,760 hours of
operation per year. The following equation in map calculator was used to create
the annual energy grid in units of kWh from the electrical power grid:
[Electrical Power Grid].Value*8760*1000
Calculate Annual Energy Value
The annual energy production grid,
designated [Energy Production Grid], is multiplied by the economic value,
designated [Energy Price], of the energy to compute the annual energy value
produced by a single turbine. The following equation in map calculator was used
to create the annual energy grid in units of kWh from the electrical power grid:
[Energy Production Grid].Value*[Energy Price]
Perform Simple Payback Analysis
The annual energy value grid,
designated [Energy Value Grid], is used with the total capital investment cost
of the wind turbine, designated [Investment Cost], to compute the simple payback
period. The economic analysis computes the period for recovery of the initial
capital investment neglecting operations costs which are considered minimal. It
also does not account for the time value of money over the payback period. The
following equation in map calculator was used to create the simple payback
period grid in years:
[Investment Cost]/[Energy Value Grid].Value
Methods of Calculating the Modification of Wind Speed Due to
Altitude
Two methods for the calculation of wind speed were presented in the
Equations Used section. The Power law relates the speed to the height assuming a
low surface roughness. It provides an easy method for calculating the wind
speed. The logarithmic velocity distribution provides a more complex evaluation
and is suited well for GIS application. The procedure for the use of the Power
Law was explained above. The logarithmic velocity distribution procedure for
wind speed modification will be explained hitherto. This procedure was developed
for potential use with the energy evaluation program, but was not used in the
energy evaluations due to the data size of the files for full coverage of Texas.
Memory constraints precluded use of this method for the overall evaluation.
Logarithmic Velocity Distribution
This method of wind speed
adjustment for altitude is based on land characteristics. These characteristics
were developed for this project from the EPA Land Use/Land Cover (LULC) files.
First, the two files retrieved for central Texas were merged. Selecting the
File/Extensions while the project file is active, the Geoprocessing extension
was clicked on. From View/Geoprocessing Wizard, the Merge Feature Data File
command was selected. The script creates a merged LULC theme.
Conversion to a grid theme is required in order to perform the necessary map
calculations. Selecting the merged theme, the Theme/Convert to Grid command was
initiated. Next, the file requires conversion to the Texas State Mapping
System projection from its current projection in Albers Conical Equal Area.
Selecting the File/Extensions while the project file is active, the Projector!
extension was clicked on. Clicking the Change Projection button, the initial
projection parameters and the desired output parameters were added. See Data
manipulation section for those parameters. The LULC theme is now ready for map
calculations.
The surface roughness assignments that were correlated to the Anderson Land
Use Codes of the LULC files are displayed in the Equations Used section. The use
of Analysis/Map Calculator calculates the surface roughness using Boolean
operators to match these correlations and develop a grid.
With the surface roughness grid, the logarithmic velocity equation was used
to develop a grid for the shear velocity. The following Map Calculation window
shows how the equation was manipulated to determine the shear velocity. The
unmodified wind speed grid and its associated height of 10 meters are used to
calibrate the equation.
Since the shear velocity grid and surface roughness grid are completed, all
parameters are determined. The equation now relates altitude with wind speed.
Using an assumed altitude of 20 meters, a modified velocity grid was calculated
using Map Calculator.
Application of Data: Develop State Map of
the Electricity Generated for a Single Small Turbine
The procedure listed
under the Wind Energy Map Calculations was run through twice. The two
run-throughs of the evaluation were completed based on a set of conservative and
a set of optimistic assumptions. For the conservative set of assumptions, a
lower range overall efficiency, 28%, and electricity value, $0.05/kWh were used.
Under optimistic assumptions, an overall efficiency of 35% and an electricity
value of $0.08/kWh were used. Electricity values were estimated using the fee
structure from the Austin Energy Company(http://www.electric.austin.tx.us/).
The generated maps for the two runs are presented below.
Annual Energy Value Maps
Conservative Run
Optimistic Run
The legend for the above maps is shown below. The units
are in $ per year.
Economic Analysis: Simple Payback Period Maps
Conservative Run
Optimistic Run
The legend for the above maps is shown below.
The units are in years.
Interface Program: Wind Resource Assessment
(MS Visual Basic)
The goal of the Wind Resource Assessment program is to
provide an interface to ArcView which allows the program user to request energy
production and its associated economic value for a specific turbine at a
specified location in Texas. The program has been developed up to the stage
where the output file of the selected parameters is created. After the initial
start screen, the Criteria Selection window appears and displays default
values for the location type to select by, the location name, the wind turbine
height, and the time period of the analysis.
From the Criteria
Selection window, there are buttons to access the economic and turbine
assumptions in order to modify these assumptions. In the Wind Turbine
Assumptions window, the turbine parameters that can be modified are
assigning a name, rotor diameter, and an overall efficiency.
In the Economic Assumptions window, the capital cost of the system,
the annual operations cost, and the price of electricity are all parameters that
can be modified.
The selected parameters are gathered and exported to an output file that can
be read by an ArcView script.
Conclusions
The wind resources maps for
the state of Texas were developed based on the ASCII Raster datasets of wind
speeds developed by the VEMAP Project. The panhandle of Texas has some of the
best areas for wind resources. Not suprisingly, it is the location where the
most wind energy research and evaluations are being conducted. During the summer
and fall, the majority of the state from the east through the central region and
south and to the west has a mean wind speed less than 4.0 m/s, which shows
little promise for reliable wind energy. For example, the small turbine selected
for the application of data section has a cut-in speed of 3.6 m/s. This means
the turbine will only run when speeds are greater than this value.
The wind energy potential of a single turbine, its associated value, and an
economic analysis were evaluated. A small wind turbine designed for domestic
applications was used to run through the evaluation. Two runs based on
optimistic and conservative parameters yielded a range of energy productions and
values. In the annual energy value calculation, the higher areas of the state
had estimates of $200 to $250 of energy production per year. The payback periods
calculated to recover the turbine capital cost showed even under optimum
conditions a poor return economically. The best payback period in the state was
17 years whereas the worst approached 140 years. These payback periods reflect
that purchasing the specified wind turbine is not a good investment from an
economic standpoint. Since the size of the selected turbine was quite small, the
evaluation suffers from the problem of economies of scale. The use of a larger
size turbine may be beneficial to depending on circumstance. The energy produced
may be more than required, but if there is a electric grid connection, the
additional energy can be sold to the local power company. More evaluations need
to be conducted to determine the feasibility of domestic wind turbines.
Finally, the Wind Resource Assessment program has been developed to provide
an interface to ArcView. The scripts for ArcView are now required to perform the
task outlined in the procedure for evaluating wind energy from wind speed grids.
Future Work
The foundation for the development of a
program that interacts with ArcView has been completed. The Wind Resource
Assessment program creates an ASCII data output file that contains location,
turbine, and economic parameters selected by a user that can be read through
running a script in ArcView. The scripts to take this datafile and perform
the necessary commands in order to return an output file that can be read by the
Visual Basic program have not been developed yet. The functionality of the
script would begin with opening the output file created by the VB program and
extract the parameters. Next, the parameters would be utilized to locate the
themes in ArcView and perform a lookup of the cell values at the location
requested. The cell value data would be written to an output data file and
returned to the program for final calculations of energy production. The
necessary code for the VB program would also be developed at that time.
Additionally, an evaluation of the logarithmic velocity distribution equation
for the determination of a modified wind speed grid should be conducted. If the
memory requirements of the land use/land cover data files for the entire state
can be reduced through reduction in resolution, this preferred method should be
established as the method of modified wind speed calculation.
The wind speed data provided in the VEMAP dataset only has wind speeds for
0.5o cells that are greater than 50% land or within the U.S.
boundaries. This has resulted in no data cells for many areas along the
eastern coast and the southern border of Texas. A method of extrapolation would
be inaccurate especially for coastal areas since wind speeds typically increase
in these areas. The best solution for this problem is the use of a higher
resolution dataset, such as that developed by Pacific Northwest National
Laboratories (which is currently unavailable on the internet).
References
Holley, E.R. and Rumer, R.R.,
Introduction to Environmental Fluid Mechanics, unpublished, 1998
Jenkins, Nicholas and Walker, John F., Wind Energy Technology, John Wiley
& Sons, 1997
Stull, R.B., An Introduction to Boundary layer Meteorology, Kluwer Academic
Publishers, Boston, 1998
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