Integrating Southwest Power Pool Wind to Southeast Electricity ...

more likely to be turned off during the night in high wind days when balancing requirements are
shared.
Scenario #4 – Effect of Removing Hurdle Rates
The only difference between Scenarios #3 and #4 is that hurdle rates are removed from Scenario
#4. It was shown previously, that production costs are only slightly reduced with Scenario 4,
while generation was shown to change mainly in SPP and SBA. Table 5-11 shows the change in
generation for Scenario #4 relative to #3. Hurdle rates around SBA are highest, and therefore
SBA would be expected to show the greatest change. SPP increases CC and coal usage as these
are modeled as cheaper (cheaper fuel price, better heat rates assumptions). SBA has
correspondingly more expensive CCs and coal units. This has the effect of increasing total
interchange into SBA and out of SPP. While removing hurdle rates completely may not be
reasonable or likely (in fact they may increase as more transmission is built for wind), it does
show the bookend of what reduced rates may do in terms of impact of balancing high amounts of
wind.
Table 5-11: Difference** in average generation for Scenario 4 vs. Scenario 3
Change in
SERC SERC
GW EES TVA SBA SPP West East Total
CC 0.12 0.34 (1.05) 0.66 (0.15) (0.01) (0.09)
GT 0.00 0.01 (0.02) 0.00 0.01 0.03 0.02
Hydro - - - - - - -
Nuclear 0.00 - - 0.00 - 0.00 0.00
Coal (0.01) (0.09) (0.57) 0.92 (0.15) 0.01 0.11
Gasoil 0.01 - (0.00) (0.00) - 0.00 0.01
Wind - - - - - - -
Other (0.00) (0.01) (0.08) 0.02 (0.00) (0.03) (0.10)
Total 0.12 0.25 (1.72) 1.60 (0.29) 0.00 (0.04)
**Positive value represents increase in generation in Scenario #3 relative to Scenario #2.
Scenario #1 Proxy – Effect of Forecast Uncertainty and Increased Reserve
Requirements Associated with Wind
The scenario 1 proxy uses only the reserve requirements from the 7 GW wind case examined
earlier. Additionally, wind is assumed to be perfectly forecast. This case is analyzed to evaluate
the balancing costs that wind imposes on the system. While this does not give so-called
‘integration costs’ of wind, it does show the effect of intra-hour variability and uncertainty. This
can be used to place other costs in context. As shown earlier, the cost reduction from higher
cooperation across the footprint is larger than that which could be achieved with smaller
balancing areas if wind could be perfectly forecast and had no intra-hour variability.
The change in the average generation between the Scenario #1 and the Proxy case is shown in
Table 5-12. As expected, the largest change is in SPP, which carries all of the intra-hour
reserves for the wind in Scenario #1. Due to reduced reserve requirements, SPP CC generation
decreases and coal is increases slightly. Coal also increases elsewhere in the region reducing SPP
exports. Looking at the costs savings shown and placing them in context of savings per MWh of
wind it can be seen that the balancing costs of the wind come to approximately $5/MWh, which
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