PROGRAM INFORMATION

PADRONI - 12/30/2011 to 5/9/2012

CSU ALP Install Team: Andrew Costinett, Jacqueline Hess, Christian Knapp, and Mike Kostrzewa

DATA DETAILS

December 30, 2011 to May 9, 2012:

The anemometer tower was installed on December 30, 2011. The site is located in Logan County in a field on top of a large hill about 2 miles SSE of the town of Padroni. The terrain is a rough pasture, with good access to the wind from all directions except from the southeast, where a copse of trees and house/garage are located about 400 feet from the tower location.

Data is collected using three (3) NRG #40C Calibrated Anemometers and one (1) NRG #200P Wind Vane, as follows:

• Anemometers
  1. 34 m (111 feet) on an NRG 60" standard boom
  2. 34 m (111 feet) on an NRG 60" standard boom
  3. 19.86 m (65.17 feet) on an NRG 60" standard boom
• Wind Vane
  1. 34.8 m (114.2 feet) heading 166° on an NRG 60" standard boom with the null point facing toward the tower

There was also a temperature sensor at a height of 1.8 m (6 feet) on a 6" boom.

All sensors feed into an NRG Symphonie data logger. The certifications for the anemometers are as follows:

The data logger generates wind reports for each day. Using the Symphonie Data Retriever software, each day's data is complied into one large data file. A zipped file that contains all of the NRG data files and a text version of the aggregate data for all days are given below:

It is important to note that these are the raw files include the offsets for the wind vanes so no compensation is required.

Experienced users may also wish to download the site file used to process the raw data with the Symphonie Data Retriever software. You can find the site file here.

From the collected data, an analysis of the wind resource report was developed for entire data collection period using Windographer 2.4.6. Since the data set contains data for two or more wind speed sensors at different heights above the ground, Windographer considered the wind shear relationship between different wind speed sensors to extrapolate the data to different heights. A best fit using the power law profile was chosen to extrapolate the data.

Using this data, an analysis of the wind resource report was developed and the data was flagged for icing in two ways:

1. Any wind speed data (from any anemometer) where the wind speed was less than 0.5 m/s at a temperature less than 0°C for 2 hours or more was flagged and ignored when calculating the wind resource statistics.
2. Any wind direction data where the wind direction varied by less than 3 degrees at a temperature less than 0°C for 2 hours or more was flagged and ignored when calculating the wind resource statistics.

The summary report, the combined data files, and the Windographer files (with and without the data quality analysis) are given below:

• Padroni_4003_2011_1231_to_2012_0509_Summary_Report.pdf
• Padroni_4003_2011_1231_to_2012_0509_without_data_validation.windog
• Padroni_4003_2011_1231_to_2012_0509_without_data_validation.txt
• Padroni_4003_2011_1231_to_2012_0509_with_data_validation.windog
• Padroni_4003_2011_1231_to_2012_0509_with_data_validation.txt

Interim Wind Resource Summary

Highlights of the wind resource to date at this site are shown below:

Windographer was used to match up the wind at this site with the performance curves of some common turbines of various sizes and various heights. The table below shows the results. For the larger turbines, the tower height was increased to account for the larger turbine blades - the wind resource was extrapolated to these higher heights. Keep in mind that the larger and the higher the turbine, the better the wind and the greater the output. But of course, as the tower heights and turbine sizes increase so does the cost.

Keep in mind too that listing a particular turbine doesn't imply an endorsement - not does it imply that installing a particular turbine model is feasible or recommended for a particular site. For consistency, the larger turbines are included even at sites that where they may not be practical so that one can compare the relative production of different sites.

IMPORTANT: No turbine losses are included in the power, energy, and capacity factor values in the table. Typically, turbine losses can be 5-20% to account for maintenance downtime, icing/soiling and losses from other turbines in a wind farm. Users wanting to be conservative in the performance projections should multiply the power, energy, and capacity values by (1- % losses) to account for these losses.

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