A Comparison of Tower to Rooftop Monitoring and Resulting Estimated Performance Andrew Kurtz – APRS World, LLC.

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Presentation transcript:

A Comparison of Tower to Rooftop Monitoring and Resulting Estimated Performance Andrew Kurtz – APRS World, LLC

Why Collect Data? To determine a site’s wind resource To determine the economic feasibility of installing a wind turbine A Poorly Sited Turbine: –Results in an unhappy customer –Is bad business –Hurts the industry

Mick’s Site

How was the data collected? Anemometers Data Loggers

Notes about the data Recorded to memory card 1 CSV (spreadsheet) file per day Tilt-up Tower – Since Nov Rooftop – Since Dec 2009 Result: over 3,200 files More than 4.6 million rows of data… That’s a lot of data!

Data Processing Reduce the data to a common working set –Only days with a full day’s worth of data from both data loggers –Detect equipment problems or other possible issues such as anemometer icing Anemometer A shows 20 to 30 MPH readings throughout the day Anemometer B shows 0 MPH readings all day

Working with databases Easier to work with large quantities of data Example, average wind speed: mysql> SELECT ROUND(AVG(wsTower74),1) FROM towerData; Result: 10.7 (MPH) Possible to do more complex operations such as frequency distributions

Average Wind Speeds

Wind Speed Frequency Distribution

Ratio of Available Energy

Estimated Annual Energy Production Turbine A – 1.1m rotor diameter

Estimated Annual Energy Production Turbine B – 3.7m rotor diameter

Estimated Annual Energy Production Turbine C – 7m rotor diameter

Conclusions Different locations on the same property show significantly different wind resource You don’t truly know the wind resource for a particular location without collecting data The results speak for themselves: Proper siting on a sufficiently tall tower is critical to wind turbine performance web: