Energy Production Potential of Wind Resources in Texas

By:  Todd J. Schram

tjschram@mail.utexas.edu

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: 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: 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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