Technical Report

NREL/TP-500-44348

May 2009

Summary Report of Wind 

Farm Data

September 2008

Yih-huei Wan
National Renewable Energy Laboratory

1617 Cole Boulevard, Golden, Colorado 80401-3393

303-275-3000 • www.nrel.gov

NREL is a national laboratory of the U.S. Department of Energy

Office of Energy Efficiency and Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC

Contract No. DE-AC36-08-GO28308

Technical Report

NREL/TP-500-44348

May 2009

Summary Report of Wind 

Farm Data

September 2008

Yih-huei Wan

Prepared under Task No. WER8.5001
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1

Summary Report of Wind Farm Data

September 2008

Yih-huei Wan

Executive Summary

The National Renewable Energy Laboratory (NREL) began a project to collect wind power plant 

output data from several large commercial wind plants during the spring of 2000. The first wind 

power plant to participate in the project was the Lake Benton II Wind Power Plant connected to 

Xcel Energy’s transmission system in southwest Minnesota. NREL installed recording and 

communication equipment on site to transmit data back to NREL. The equipment recorded real 

and reactive power outputs and 3-phase line-to-ground voltages at the wind plant interconnection 

point at a 1-Hertz sampling rate.

Since then, the number of wind plants participating in the project has gradually increased to 

include wind power plants in Iowa, Oklahoma, and Texas. In addition to the data collected by the 

recording equipment installed by NREL at the wind power plants, the project solicited historical 

wind power data of lower resolution (1-minute, 10-minute, and hourly) from utilities and plant 

operators/owners to reduce the cost of the program. All together, the project has collected data 

from more than 25 wind power plants with a total installed wind generating capacity of more 

than 4 GW. The majority of the data are 1-minute real power time-series data from Texas wind 

power plants beginning in 2004.

The purpose of collecting these data is to (1) investigate the behavior of wind power and its 

statistical properties, (2) analyze the spatial and temporal correlation of wind power, (3) validate 

wind plant and wind forecasting models, and (4) make actual wind power time-series available 

for standard utility planning and operating study models to evaluate the impacts of wind power

use on the electrical grid.

The data collected by NREL have been used in several pioneering wind power integration 

studies to quantify the impacts of wind power on grid operations and ancillary services. However, 

as installed wind power capacity continues to increase rapidly, so does the need to expand the 

scope of data collection activities to include wind power plants in more geographically diverse 

regions. It is more critical to capture and to better understand spatial diversity of wind power and 

how it correlates with regional load patterns at higher wind power penetration levels. More 

importantly, as NREL launches its mesoscale modeling tasks for its western and eastern wind 

integration studies, it will need more historical wind power data to validate and calibrate the 

wind plant output models used to generate wind power time series for the United States.

To establish a long-term wind power database, the wind plant data collection project will 

continue. To expand the scope of the project, NREL will focus on working with utilities and 

wind power plant operators/owners to retrieve the desired data from the utility energy 

management systems (EMS) and wind plant supervisory control and data acquisition (SCADA)

systems.
2

Introduction

Wind power plants are different from conventional central-station power plants with large 

synchronous generators because wind power output is variable and, in general, cannot be 

controlled by operators. This is one of the main reasons utilities have been reluctant to include 

wind power in the past. Despite the tremendous growth of wind power in this country, most 

utilities still do not have experience in integrating wind power into their standard planning and 

operating processes. At very low penetration levels, the impact of wind power on utility planning 

and grid operation is mostly negligible because the natural fluctuations of the utility load

overwhelm any variations of wind power. As wind power’s share in the generation mix grows, 

its operations will have a greater impact on local grid operations in some regions, and utilities are 

concerned about system reliability and regulation requirements. Utility operators and planners 

need data and models to analyze the impacts of integrating wind power into the grid and to plan 

mitigation strategies if necessary. NREL’s wind plant monitoring project is designed to 

systematically collect long-term, high-resolution wind power data to satisfy this need.

NREL works with wind power plant owners/operators and utilities to gain permission to install 

data loggers at the points of interconnection to record wind power data or to transmit the wind 

power data directly from the utility EMS to NREL.

Scope of the Wind Farm Data Collecting Activities

Table 1 lists the wind power plants that are providing data for the project using equipment owned 

by NREL. Data from these sites are recorded at a rate of 1-Hz and are downloaded daily. Data 

availability is affected by forced outages of field equipment and communication links.

Table 1. Wind Power Plants Monitored with NREL Equipment.

Name Location Turbine

Manufacturer

Turbine

Size

Total 

Cap.

Starting 

Year

Lake Benton Lincoln County, MN Zond Z50 750 kW 103 MW 2000

Storm Lake Buena Vista County, IA Zond Z50 750 kW 113 MW 2001

Buffalo Ridge Pipestone County, MN Zond Z501 750 kW 240 MW 2001

Texas Wind Power Project Culberson county, TX Kenetech 330 330 kW 35 MW 2003

Indian Mesa Pecos County, TX Vestas V47 660 kW 83 MW 2003

King Mountain Upton County, TX Bonus 1.3 1300 kW 79 MW 2003

Trent Mesa Taylor county, TX GE 1.5 1500 kW 150 MW 2003

In addition to the wind plants in Table 1, NREL also receives wind power data from utilities in 

Oklahoma, Washington, and Oregon. Data from the Blue Canyon wind power plant in Oklahoma 

are 1-minute time series and only from the first phase of the project.

2

 1 Five wind power projects feed into Xcel Energy’s Buffalo Ridge substation. The two largest projects are Lake 

Benton I and II, with Zond Z50 turbines. The others are small wind projects of 10 MW or less installed capacity.

Data from the Washington 

2 The power from the second phase of the project goes to a different utility.
3

and Oregon wind plants are 2-second historical time series. Table 2 lists the information of those

wind plants.

Table 2. Wind Power Plants with Data Provided by Utilities.

Name Location Turbine 

Manufacturer

Turbine

Size

Total 

Cap.

Starting 

Year

Blue Canyon Comanche County, OK NEG Micon 1650 kW 74 MW 2004

Stateline Walla Walla County, WA Vestas 660 kW 90 MW 2002

Vansycle Umatila County, OR Mitsubishi 600 kW 25 MW 2002

Condon Gillam County, OR Mitsubishi 600 kW 50 MW 2002

Nine Canyon Franklin County, WA Bonus 1300 kW 20 MW 2002

Klondike Sherman County, OR GE 1500 kW 40 MW 2002

In 2008, NREL began receiving historical 1-minute wind power output data for 2004 to 2007 for 

operating wind power plants in Texas from the Electric Reliability Council of Texas (ERCOT), 

the electric grid operator in Texas. Table 3 lists the ERCOT wind power plants. It should be 

noted that Table 3 only includes the wind plants that were in the ERCOT plant information (PI)

system at the end of 2007. The data were extracted directly from the wind plant SCADA systems 

or PI systems and data were not checked for errors by ERCOT. As a result, data quality is not 

consistent for all wind plants.

Table 3. Wind Power Plants with Data Provided by ERCOT3

.

Name Location Turbine 

Manufacturer

Turbine

Size Total Cap.

Brazos Wind Ranch Borden and Scurry Counties Mitsubishi 1000 kW 160 MW

Horse Hollow Wind Energy Center Taylor and Nolan Counties GE

Siemens

1500 kW

2300 kW 735 MW

Callahan Divide Wind Energy Center Taylor County GE 1500 kW 114 MW

King Mountain Wind Farm Upton County Siemens 1300 kW 278 MW

Woodward Mountain Wind Ranch Pecos County Vestas 660 kW 160 MW

Trent Mesa Wind Project Taylor and Nolan Counties GE 1500 kW 150 MW

Desert Sky Wind Farm Pecos County GE 1500 kW 160 MW

Indian Mesa Wind Farm Pecos County Vestas 660 kW 83 MW

Delaware Mountain Wind Farm Culberson County Zond 750 kW 29 MW

Texas Wind Power Project Culberson County Kenetech 330 kW 35 MW

Big Spring Wind Power Project Howard County Vestas 660 kW

1650 kW

34 MW

Southwest Mesa Wind Farm Upton County NEG Micon 700 kW 75 MW

Buffalo Gap I & II Taylor and Nolan Counties Vestas

GE

1800 kW

1500 kW

120 MW

233 MW

Sweetwater Wind Farm Nolan County Mitsubishi

Siemens

GE

1000 kW

2300 kW

1500 kW

585 MW

Camp Springs I & II Scurry County GE 1500 kW 250 MW

 3 The names of the wind power plants are from the ERCOT PI system, and they may differ from their commercially 

designated names.
4

Forest Creek Wind Farm Glasscock and Sterling Counties GE 1500 kW 124 MW

Sand Bluff Glasscock and Sterling Counties GE 1500 kW 90 MW

Capricorn Ridge Wind Farm Sterling and Coke Counties GE

Siemens

1500 kW

2300 kW

215 MW

149 MW

Lone Creek Post Oak Shackelford County Gamesa 2000 kW 200 MW

Red Canyon Borden, Garza and Scurry Counties GE 1500 kW 84 MW

Whirlwind Floyd County Seimens 2300 kW 60 MW

ENEL Snyder Wind Project Scurry County Vestas 3000 kW 63 MW

The Alberta Electric System Operator (AESO) and the Independent Electricity System Operator 

(IESO) in Ontario, Canada, have both made real-time electricity power system and market 

information, including wind generation, available on their web sites. AESO’s system supply 

report lists 10 wind power plants with a total installed capacity of 490 MW.

4 The IESO web site 

shows seven wind power plants totaling 770 MW of installed capacity.

5 Only hourly data 

streams are archived and available for download in their FTP servers. We download their hourly 

wind power data.

Of all the data recorded and collected from the different wind power plants, the plants in

Minnesota and Iowa have the highest data availability rate. The data availability rate combined 

with a good working relationship with the crews allows for quick resolution of any problems 

with equipment or phone lines, and contributed to NREL’s decision to maintain its data loggers 

and the communication links at the Minnesota and Iowa wind plants. 

Applications of the Data

High-resolution wind power data (1-second and 1-minute time series) are being used in system 

integration studies by utilities and to validate the results of mesoscale wind power models.

Standard utility planning and engineering models are used for utility wind integration studies. 

Actual wind data are used as one of the inputs to those models to evaluate how the electric 

systems will interact with wind power, and what aspect of the electric system will be impacted 

by wind power and to what degree. The following organizations have used the data collected by 

NREL in 2008 for various wind studies.

• Western Interstate Energy Board

• Platte River Power Authority

• Bureau of Reclamation Hydroelectric Power

• BC Hydro

• BC Transmission Operator

• Manitoba Hydro

 4 AESO current system information is available at http://ets.aeso.ca/ets_web/ip/Market/Reports/CSDReportServlet. 

The historical data are available at http://ets.aeso.ca/. 5 IESO information is available at http://www.ieso.ca/ and the historical data are available at 

http://reports.ieso.ca/public/GenOutputCapability/. 
5

The goal of the wind plant power-output data collection project is to make the data available to 

other researchers and utility planners performing wind studies. NREL has agreed to respect the 

proprietary nature of the wind power data collected. Therefore, when we provide data for other

organizations to use for system studies, we require that the names of the wind power plants and 

the data itself not to be published. Only statistics derived from the data can be made public.

The data are used to validate the wind power time series created for the Western Wind 

Integration Studies and Eastern Wind Integration and Transmission Studies by 3Tier and 

AWS/Truewind, respectively. Step change statistics of the wind power time-series data that is 

created are compared to similar statistics of actual wind power data collected. Model output 

statistics (MOS) corrections are applied to the created data based on the comparison. 

Outlook of Wind Plant Monitoring

Usefulness of actual wind plant output-data for studying the impacts of wind power on the 

electric grid has increased with the higher penetration level of wind power in the electric system.

Rapid deployment of installed wind power over greater areas also makes it more important to 

know the effect of wind resource spatial diversity on the behavior of wind power plants, 

especially its effect on the ramping of wind power. However, the number of new wind power 

plants and their geographic dispersion necessitate a change of our approach in collecting the data.

NREL installing and maintaining its own data loggers to collect the wind power data results in 

the highest recovery rate and quality of data, but it is not always practical in terms of cost. The 

way NREL works with ERCOT to receive high-resolution historical wind-power data directly 

from system operators represents a model for future data collection projects. Independent system 

operators (ISO) are making system information transparent to all interested parties – AESO and 

IESO are two examples. The California Independent System Operator (CAISO) also makes

system information, such as actual and forecasted load and actual generation, available on its 

public web site in real time (updated every minute). Making the archived version of such data 

available to researchers and academics can avoid proprietary data issues, which is the single 

biggest obstacle when getting data from plant owners and operators.

There are drawbacks associated with getting data from an ISO. Extracting historical data from PI 

systems takes time and represents additional work for ISOs. NREL depends on work schedules

of ISO staff to perform the data extracting task for us. The data quality is another potential 

problem. However, the cost of the alternative approach is much higher. One of the goals of the 

wind plant monitoring project is to expand the scope of the project to include wind power plants 

in California, Illinois, New York, and Pennsylvania. NREL will try to work with the California 

ISO and Midwest ISO to gain access to its archived wind power data in much the same way it 

works with ERCOT.

Currently NREL has a subcontract with Electrotek to maintain and collect 1-second output 

power data from four wind power plants in Texas. The instruments have been in the field for 

more than 6 years and their reliability has decreased noticeably; missing data points have 

increased steadily. Because NREL receives 1-minute output power data from the same wind 

power plants through ERCOT, it will consider terminating the subcontract with Electrotek and 
6

removing the data loggers and communications equipment when the subcontract is completed at 

the end of 2008.

Another big problem with wind power data collection is the lack of corresponding wind speed 

and direction data from the wind power plants. Wind power data without corresponding wind 

resource data from the same wind power plant prevents the data from being effectively used in 

wind power forecasting applications. Wind speed and direction data from wind power plants are 

not generally available because such data are considered as “business sensitive” by the wind 

plant owners and operators. Another reason for the lack of wind data is that such data often do 

not exist at many wind power plants, especially if the ISOs (through market design) or local 

utilities do not mandate that plant operators provide wind power forecasting information. After a

wind plant starts commercial operation or when the manufacturer’s warranty on the turbines has 

expired, the meteorological towers may no longer be properly maintained and calibrated, and 

wind data are not recorded because such information is not needed in daily operations. However, 

utilities are beginning to request wind power forecasting information to help with the integration 

of ever increasing wind power in their system, and more metrology tower data will become 

available. NREL will work with the ISO and utilities to obtain archived metrology tower data.

Some Observations of the Data

One observation from the available data is the significant yearly variation of wind resources. 

Figure 1 below shows monthly production at Lake Benton (Minnesota) from 2000 to 2007. 

Although a general pattern can be detected, the individual monthly production can change as 

much as 100% from one year to another.

Figure 1. Monthly production of Lake Benton wind power plant.

Figure 2 plots the monthly production of wind power plants near McCamey, Texas. Only data 

from plants that have been in operation since the beginning of 2004 are included. The pattern is 

even less clear in Figure 2. These significant yearly variations of wind power points to the need 

for a long-term data recording program so that the extent of such variations can be better 

Lake Benton Monthly Production

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

MWh

2000 2001 2002 2003

2004 2005 2006 2007
7

understood, and mitigation strategies can be included in the system planning process. Compared 

to the nation’s hydropower production that customarily references 30-year or even 50-year mean 

and standard deviation values, wind power does not have long-term statistics that can be 

confidently used in the system planning process. New extreme values or events seem to appear 

every year. One reason is the rapid growth the wind industry is experiencing, but this does not 

diminish the importance of long-term data.

Figure 2. Monthly production of wind plants near McCamey, Texas.

Figures 1 and 2 show other important characteristics of wind power – the spatial and temporal 

diversity. It is expected that outputs from wind plants separated by long distance will be diverse, 

and the data support this expectation. Minnesota wind production tends to peak in late winter and 

early spring months. Texas wind plants also produce more energy during these month, but they 

tend to peak in late spring months. In addition, the peak production days of Minnesota and Texas 

wind plants did not coincide during the 2004-2007 period. The days of low wind generally 

happen during summer months in Minnesota, but not in Texas. The minimum production days do 

not coincide during the 2004-2007 period either.

Aggregating outputs from many wind power plants will smooth out the overall output power 

profile. The effect was dramatic when the 2007 data from all Texas wind power plants were

summed. Table 4 shows the mean and standard deviation values of the magnitude (absolute 

values) of hourly step changes, expressed in relation to installed wind power capacity. When all 

available power data are combined, average step changes and its standard deviation decrease

significantly, as expected. 

Monthly Production Around McCamey, Texas

0

24,000

48,000

72,000

96,000

120,000

144,000

168,000

192,000

216,000

240,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

MWh

2004

2005

2006

2007
8

Table 4. Average and Standard Deviation Values of Hourly Ramping of Three Wind Plants

Brazos 1(84 MW) Lubbock (244 MW)6 All Wind Plant(>3 GW)7

2007 Avg. St. dev. Avg. St. dev. Avg. St. dev.

Jan 5.1% 7.5% 3.4% 3.9% 0.7% 0.4%

Feb 5.3% 7.8% 3.7% 3.7% 0.7% 0.4%

Mar 7.2% 7.7% 4.9% 4.0% 0.7% 0.4%

Apr 6.9% 7.2% 4.9% 3.9% 0.7% 0.4%

May 6.0% 7.4% 4.3% 4.1% 0.7% 0.4%

Jun 6.9% 8.1% 4.4% 4.0% 0.7% 0.4%

Jul 4.8% 6.4% 3.8% 3.8% 0.7% 0.4%

Aug 5.6% 6.4% 4.3% 3.8% 0.6% 0.3%

Sep 6.3% 7.2% 4.7% 4.1% 0.5% 0.3%

Oct 4.8% 6.4% 3.5% 4.0% 0.4% 0.4%

Nov 6.3% 7.2% 4.3% 3.6% 0.5% 0.3%

Dec 7.3% 7.8% 4.3% 3.5% 0.5% 0.3%

The distribution of hourly step changes is shown in Figure 3. It can be seen that 91.4% of all 

hourly changes are less than 300 MW in magnitude (roughly 10% of the wind capacity), and 

99.2% of the hourly changes are less than 600 MW in magnitude (20% of the wind capacity). 

However, the data also reveals that there were 8 occurrences (0.1% of all hourly changes) of 

hourly changes of 900 MW in magnitude or greater. One occurrence of large hourly changes 

occurred on October 21, 2007. Figure 4 plots the 1-minute average power profile for that day.

Figure 3. Distribution of hourly wind power changes.

 6 Combined output of wind power plants near Lubbock, including Brazos 1 and 2 and Red Canyon, with a total 

capacity of 244 MW.

7 All 2007 data from ERCOT are combined. The total capacity increased significantly during the last 5 months of 

the year. The percentage values are calculated with a monthly capacity value.

Distribution of Hourly Step Changes

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

-1000 -900 -800 -700 -600 -500 -400 -300 -200 -100 0 100 200 300 400 500 600 700 800 900

Step Changes (MW)

Frequency
9

Total wind power actually dropped from a morning high of 2.8 GW to a low of 0.66 GW, and 

then increased to 2.8 GW again in the evening during a 20-hour period – a swing of more than 

2.2 GW. Between the hours of 17:00 and 18:00, wind power was ramping up at a rate of 1.6 GW 

per hour. Although such large swings happen infrequently, they may cause difficulties in system 

operations.

Figure 4. Daily 1-minute average power profile.

Total Texas Wind Power Profile

October 21, 2007

0

500

1,000

1,500

2,000

2,500

3,000

0:001:002:003:004:005:006:007:008:009:00

10:0011:0012:0013:0014:0015:0016:0017:0018:0019:0020:0021:0022:0023:00

Time (hh:mm)

(MW)
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Summary Report of Wind Farm Data: September 2008

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Yih-huei Wan

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14. ABSTRACT (Maximum 200 Words)

The National Renewable Energy Laboratory (NREL) began a project to collect wind power plant output data from 

several large commercial wind plants during the spring of 2000. This data is summarized in this report.

15. SUBJECT TERMS

Wind; power; plant data; forecasting; Minnesota; Texas; Iowa; Oklahoma; Oregon; Washington; Xcel; performance;

wind plant monitoring.

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