Chapter 4.1: Over all Performace

Of course the output is entirely dependant on the wind available.  The  Ontario Government has these two maps of wind speed in the Province (see)

Of course, this is over all for the year, and obviously, as you will see below and in subsequent chapters, changes radically in the summer from “optimal” performance.

The over all wind output on a percent Hourly Capacity Factor vs number of hours for all turbines looks like this:

Not all the wind farms started at the same time.  This is the beginning time and number of records used to make that graph.

WindFarm Capacity MinOfDate MaxOfDate CountOfHour
AMARANTH 200 01-Mar-2006 26-Aug-2010 39360
KINGSBRIDGE 40 01-Mar-2006 26-Aug-2010 39360
PORT ALMA 101 19-Jul-2008 26-Aug-2010 18456
PORT BURWELL 99 20-May-2006 26-Aug-2010 37440
PRINCEFARM 189 08-Oct-2006 26-Aug-2010 34056
RIPLEY SOUTH 76 02-Dec-2007 26-Aug-2010 23976
UNDERWOODWGS 182 29-Nov-2008 26-Aug-2010 15264
WOLFE ISLAND 198 13-May-2009 26-Aug-2010 11304

The plot only uses the number of hours of existing data to get the Hourly Capacity Factor, including hours of no output.

Notice the large number of hours of no output.  At 15.8% of the hours it dominates the plot.  The next column (between .09 and 1.0 % name plate) which is the second largest number of hours, is a mere 3.9% of the hours.

You can clearly see that the average, what the industry uses for Capacity Factor, has no physical meaning on this plot.  It’s not in the middle, it’s not exceptional, it’s not unique in any way.  It’s just a calculation of the average.

The median, however, is the point where half the hours are below that value.  Overall then, the median of 14% means this:  Fifty percent of the time output from wind in Ontario is less than 15% name plate.  Half the time the output is 14% OR LESS. From this point on this point will be referred to as the Median Capacity Factor.

The other significant number here is the Standard Deviation.  65% of all values are in the first Standard Deviation noted on the graph.  That number is the Median plus the Standard Deviation of 27.4%.

Skewness is a complex calculation (see), but important number because it tells us how far the median is from the average.  Consider it the “pull” on the bell curve in one direction.  A positive number is to the left, towards smaller percent of name plate.  If the skewness was negative, the median would be to the right of the average, more into the high percent of name plate.

This graph shows the changes in the Capacity Factor (not the Median Capacity Factor) for all the farms over each month.  The Median Capacity Factor (where 50% of the time output is lower) is about half these numbers.

Notice the significant drop off in Capacity Factor during the summer months.  Fall 2009 to 2010 was a particularly low year for wind production.

This graph is the Median Capacity Factor for each month for each farm.  The summers clearly show very low MCF below 10% for almost all the farms.   In the summer time, all the farms half the time produce less than 10% name plate.  Notice some of the winter months come very close to the Capacity Factor, which will show up as near zero skewness for that month.

This plot of skewness per farm per month is the opposite of the above graphs.  Very low skewness in the winter months, but very high skewness in the summer.  This means that in the summer time the use of Capacity factor is further away from actual output.  The spread of the output for each month, the range of the Hourly Percent Name Plate, is the Standard Deviation.

Notice that the range of values is much more spread out in the winter (higher SD) than in the summer.

So summers tend to be small MCF, with high skewness and narrow range of hourly percent name plate output, while winters tend to be higher MCF, with low skewness (closer to the CF), but with a very wide range of hourly name plate values (thus more intermittent and with unpredictable swings than in the summer).

This is the data that produced the top graph:

 HCF Count Of Hours Accum Hours % of the time 0 34634 34,634 15.8% 1 7790 42,424 19.4% 2 9206 51,630 23.6% 3 6002 57,632 26.3% 4 4798 62,430 28.5% 5 6830 69,260 31.6% 6 5036 74,296 33.9% 7 6247 80,543 36.7% 8 3678 84,221 38.4% 9 3828 88,049 40.2% 10 5411 93,460 42.6% 11 3697 97,157 44.3% 12 4391 101,548 46.3% 13 3491 105,039 47.9% 14 3154 108,193 49.4% 15 4365 112,558 51.3% 16 2354 114,912 52.4% 17 4017 118,929 54.3% 18 2434 121,363 55.4% 19 2659 124,022 56.6% 20 3195 127,217 58.0% 21 2351 129,568 59.1% 22 3234 132,802 60.6% 23 2223 135,025 61.6% 24 1826 136,851 62.4% 25 3065 139,916 63.8% 26 1958 141,874 64.7% 27 2551 144,425 65.9% 28 2074 146,499 66.8% 29 1330 147,829 67.4% 30 2699 150,528 68.7% 31 1751 152,279 69.5% 32 2575 154,854 70.6% 33 1103 155,957 71.1% 34 1411 157,368 71.8% 35 2065 159,433 72.7% 36 1124 160,557 73.2% 37 1792 162,349 74.1% 38 1118 163,467 74.6% 39 1181 164,648 75.1% 40 1750 166,398 75.9% 41 893 167,291 76.3% 42 1764 169,055 77.1% 43 1021 170,076 77.6% 44 993 171,069 78.0% 45 1302 172,371 78.6% 46 950 173,321 79.1% 47 1506 174,827 79.8% 48 855 175,682 80.1% 49 620 176,302 80.4% 50 1422 177,724 81.1% 51 938 178,662 81.5% 52 1425 180,087 82.2% 53 800 180,887 82.5% 54 540 181,427 82.8% 55 1231 182,658 83.3% 56 800 183,458 83.7% 57 1283 184,741 84.3% 58 554 185,295 84.5% 59 738 186,033 84.9% 60 1184 187,217 85.4% 61 710 187,927 85.7% 62 1064 188,991 86.2% 63 628 189,619 86.5% 64 677 190,296 86.8% 65 1125 191,421 87.3% 66 541 191,962 87.6% 67 1111 193,073 88.1% 68 662 193,735 88.4% 69 634 194,369 88.7% 70 871 195,240 89.1% 71 651 195,891 89.4% 72 1025 196,916 89.8% 73 698 197,614 90.1% 74 511 198,125 90.4% 75 1126 199,251 90.9% 76 670 199,921 91.2% 77 1017 200,938 91.7% 78 641 201,579 92.0% 79 484 202,063 92.2% 80 1116 203,179 92.7% 81 608 203,787 93.0% 82 1155 204,942 93.5% 83 459 205,401 93.7% 84 594 205,995 94.0% 85 1297 207,292 94.6% 86 687 207,979 94.9% 87 1143 209,122 95.4% 88 700 209,822 95.7% 89 776 210,598 96.1% 90 1606 212,204 96.8% 91 639 212,843 97.1% 92 1990 214,833 98.0% 93 873 215,706 98.4% 94 767 216,473 98.7% 95 1048 217,521 99.2% 96 703 218,224 99.5% 97 422 218,646 99.7% 98 568 219,214 100.0% 99 0 219,214 100.0% 100 1 219,215 100.0%