Integrating Southwest Power Pool Wind to Southeast Electricity ...

site selection could have congregated the plants for each of regions in a smaller area, correlating
the output to a higher degree and resulting in higher variability. This has direct consequences to
the results of the study since the lower the variability, the lower the balancing requirement for
wind. This assumption of higher diversity tends to reduce the inter-BA cooperation benefits that
are calculated later.
To illustrate, Figure 3-3 shows these diversity effects for an example set of plants from the actual
data used in the study. Using the standard deviation of the 10 minute change in aggregate output
as a metric, the variability of eight concentric aggregation areas is examined. The smallest is a
single 100 WM plant moving in steps to the largest of a 12000 MW regional aggregation. Note
that variability drops from more than 4.5% for the single plant to about 1% for the largest
aggregation area.
This aggregation has a direct effect on reserve requirements and ramping duty seen by the entity
who balances the wind. If the wind is rising in one portion of the aggregation area, as the size of
the area increases, it is much more likely that it is decreasing in another portion to reduce the size
of the net change.
Normalized 10 minute Sigma
5.0%
4.5%
4.0%
3.5%
3.0%
2.5%
2.0%
1.5%
1.0%
0.5%
0.0%
Effect of Geographic Diversity and Aggregation on Variability
Normalized to Aggregate Wind
0 2000 4000 6000 8000 10000 12000 14000
Total Aggregated Nameplate (MW)
Figure 3-3
Effect of diversity and aggregation on variability
Wind Characteristics
With the wind plants selected and assigned to the four study regions, aggregate wind data can be
calculated and characteristics computed. Table 3-2 shows these characteristics tabulated with the
coincident total and non-coincident total for the entire footprint.
3-4