Julia Austin Posted May 14, 2009 Report Share Posted May 14, 2009 AWEA Windpower 2009 Presentation V5-12-09.pdf "Investigation of the NRG #40 Anemometer Slowdown" Presented 7 May 2009 by Steven Clark, Mechanical Engineer, NRG Systems, Inc. AWEA WINDPOWER Conference and Exhibition 2009, Chicago, IL Link to comment Share on other sites More sharing options...
kldgreen Posted September 16, 2009 Report Share Posted September 16, 2009 Can you elaborate on the specifics for the quantitative statistics used to identify sensor error? For clarity: mean bias = difference between two means of the (10 minute) averages for a 7 day period ratio = ratio of the means of the (10 minute) averages for a 7 day period correlation coefficient = corr coeff between the 2 sets of (10 minute) average wind speeds over the 7 day period st dev wind speed ratio = std dev of the ratios of the (10 minute) average wind speeds over the 7 day period Thanks in advance for the help! Link to comment Share on other sites More sharing options...
Julia Austin Posted September 18, 2009 Author Report Share Posted September 18, 2009 You will need to analyze several months of data ? at least 4 ? 8 months, ideally ? in order to detect a potential problem. You?ll need to compare wind speed data from pairs of sensors at the same height on the tower, excluding any wind speed data potentially affected by tower shadowing or shadowing due to nearby structures and/or terrain features. Your best bet may be to contact which ever consulting company you normally work with for data analysis as they have the expertise in scrutinizing the data at this level of detail. They are likely already familiar with the problem and how to find it in the data, and they may also be able to provide some recommendations about how to treat any potentially affected data. When we have been looking at our research data, we were sorting data from redundant, same height, un-shadowed sensors as follows: Mean Bias: 0.2 Ratio: 1.02 Ratio SD: > 0.02 R Value: However, this is not based on some established standard, nor are we advocating these as appropriate criteria for any and all data sets. These criteria, for example, do not take into consideration the effects of complex terrain. Unfortunately the nature of this problem and the vast variation among sites makes it very difficult to recommend a standard way of dealing with the data. I hope this helps. Link to comment Share on other sites More sharing options...
kldgreen Posted September 19, 2009 Report Share Posted September 19, 2009 Yes, thank you but the response does not answer my original question. I'm looking for more description of exactly how the four quantiative stats above are calculated; especially for ratio SD... do you calculate the ratio of each 10 minute average over the 7 day period and then take the standard deviation of that or some other method? Please if you can provide clarity on this that would be great. Thanks! Link to comment Share on other sites More sharing options...
johng Posted September 21, 2009 Report Share Posted September 21, 2009 Hi - Here is some further clarification. Mean Bias Mean bias is defined as the average of the 10 minute wind speed differences between two anemometers over each week. The second sensor in the pair is subtracted from the first for each 10 minute interval. Those results are then averaged over the week. That result is the mean bias for the week. Ratio Ratio is defined as the average of the 10 minute ratios between two anemometers over each week. The first sensor in the pair is divided by the second sensor for each 10 minute interval. Those results are then averaged over the week. That result is the ratio for the week. Correlation R R is the statistical correlation of the 10 minute averages for each week, where Ch1 is the X parameter and Ch2 is the Y parameter. Ratio SD Ratio SD is the statistical standard deviation of the 10 minute ratios for each week. Link to comment Share on other sites More sharing options...
kldgreen Posted October 3, 2009 Report Share Posted October 3, 2009 yes, agreed, thanks! Link to comment Share on other sites More sharing options...
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