Data Loggers

Data loggers for wind resource measurements are now the norm. Data are stored on data chips, and either chips are retrieved or data loggers send information to a base personal computer. The BASE program monitors the phone lines, answers the call, and determines which site is calling and what is the status of the data card and call-in schedule (card unread, first call of six tries; card partially read, fourth call of six; etc.).

For time sequence data, the amount of data is large. For example, suppose you want to measure wind speeds, wind direction, pressure and temperature (1 Hz sampling rate), average values, and statistics stored every 10 min. That would be around 130 KB of data per month. A 60 min magnetic tape will store 180 KB; however, standard data chips now store 16 MB, which is around 2 years of data. You still need to retrieve the data at least once per month as a check on problems. With phones or satellite connection, data should be retrieved once per week.

The logistic problems have to be taken care of to ensure high data recovery and the quality of the data analyzed. Calibration and replacement of sensors must be part of a routine maintenance program. For example, anemometers should be replaced once per 6 months to 2 years, depending on the number of revolutions and the environment.

A quality assurance program for flagging suspect data is imperative. Data recovery should be around 95%. Sensors problems are due to failure, low/no values due to icing, lightning, and even vandalism. Data loggers and transmission problems can also lead to loss of data. Yearly failure rates are around 25% for sensors and 10% for data loggers. Rates could be higher for sites with very harsh conditions, for example, hail, lightning, dust or sandy areas, or extended periods of high winds.

Generally, there will be two anemometers and one wind vane per level with two or more levels. If one anemometer is down, there are still data from the second anemometer. If both are not operating, there is the possibility of estimating values based on data at another level and past wind shear values. So the 95% data recovery is feasible.

Wind farm developers want the average wind speed (10 min or 1 h) so they can predict energy production. Data analysis programs, which are fairly flexible, are available. As an example, the monthly average, minimums, and maximums for each sensor for the month plus selected graphs and tables are available.

EXAMPLE OF SUMMARY REPORTS AVAILABLE BY MONTH FROM AN ANALYSIS PROGRAM

Comparison of hourly wind speeds (two anemometers at same height or between different heights)

Frequency distributions (calculate wind power/area) (Figure 4.16)

Frequency distribution graph

Diurnal wind speed graph

Average turbulence intensity (upper level, use prevailing wind anemometer)

Wind rose graph

Average wind shear table (between two heights)

Average temperature graph

Data can be placed in spreadsheets for further analysis, as most data loggers allow export. Another benefit is that data analysis is not tied to a proprietary program, which sometimes even the manufacturer has trouble updating, especially if a subcontractor developed the software program.

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FIGURE 4.16 Example graph, frequency distribution plus energy, from analysis program, 50 m height, White Deer, Texas, April 1998.

Renewable Energy 101

Renewable Energy 101

Renewable energy is energy that is generated from sunlight, rain, tides, geothermal heat and wind. These sources are naturally and constantly replenished, which is why they are deemed as renewable. The usage of renewable energy sources is very important when considering the sustainability of the existing energy usage of the world. While there is currently an abundance of non-renewable energy sources, such as nuclear fuels, these energy sources are depleting. In addition to being a non-renewable supply, the non-renewable energy sources release emissions into the air, which has an adverse effect on the environment.

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