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Ancillary Services: A Call for Fair Prices

Fortnightly Magazine - January 1 2000

allocation method should reward (pay) loads that reduce the total regulation burden. A third criterion for choosing an allocation method could be one that is independent of the order in which loads are added to the system; this objective overlaps with the first one discussed above. In other words, the method should treat loads equitably, regardless of whether their standard deviations are positively or negatively correlated with each other, or independent of each other.

The regulation-allocation method we developed uses the two-minute data for each load whose regulation requirement is to be individually measured and the two-minute data for the total system. Overall system regulation requirements are then calculated with and without the load of interest. That allowed us to develop a simple method that accounts for correlations among the regulation burdens of different loads, as well as their magnitudes. It is not necessary to meter the regulation requirements of all loads. (The regulation burden of non-metered loads can be allocated assuming that the regulation burdens of these non-metered loads are uncorrelated.)

The allocation method assigned the large industrial customers an average share of regulation equal to 93 percent of the total, almost triple their 34 percent share of system load. As shown in Figure 3, there were several hours during this period when the industrial customers were assigned more than 100 percent of the regulation requirement. During the hours the industrial share exceeded 100 percent, the nonindustrial customers would have received a credit for regulation, offsetting their regulation costs during the other hours.

These results show that large, volatile loads can require a control area to acquire significant amounts of capacity for regulation. This capacity could otherwise be sold into energy or contingency-reserve markets. The results also show that most loads have much smaller effects on overall regulation requirements and therefore do not merit separate metering for regulation purposes. The method developed here applies to both types of loads.

Case B (Load Following):

Peaks, Not Volatility

Our case study shows that the need for load following is tied to regular repeating patterns in customer load profiles. Load following, like regulation, should not be billed on the basis of peak demand or size of load.

We defined the load-following magnitude (in megawatts) as the difference between the maximum and minimum values of 30-minute rolling-average load during each hour. Unlike regulation, load following is a signed quantity, positive if it is rising during the hour and negative if it is falling. Also unlike regulation, there is a clear diurnal pattern, reflecting the morning and early evening peaks and the late evening dropoff shown in Figure 1. The nonindustrial loads track closely this diurnal pattern, while the industrial load is much more erratic in its load following.

As with regulation, the correlation coefficients between load and load-following magnitude are very small, suggesting that load itself is a poor predictor of load-following requirements. Again, this implies that load-following costs should not be collected on the basis of hourly demand.

We calculated each customer's (or each group of customers') share of load following as the ratio