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The Value of Resource Adequacy

Why reserve margins aren’t just about keeping the lights on.

Fortnightly Magazine - March 2011

keep track of all production and purchase costs above the marginal cost of the new capacity resource as well as the fixed costs of the added new capacity. The analysis breaks these customer reliability costs into four categories: production-related reliability costs, reliability and emergency purchase costs, unserved energy costs and capacity resource carrying costs.

First, production-related reliability costs are defined as any costs of the system’s physical generation above the dispatch cost of the new capacity resource. This includes the dispatch of higher-cost generators such as oil-fired turbines and old natural gas turbine units.

Second, reliability and emergency purchase costs are defined as the costs of any purchases at prices higher than the cost of the marginal capacity resource. The model distinguishes between “emergency purchases,” associated with events when emergency assistance is requested from neighboring systems, and “reliability purchases,” which include all other purchases at prices higher than the cost of a marginal capacity resource. In simulations, these reliability and emergency purchase costs, including purchases associated with demand-side resources, can range from $1/MWh above the dispatch cost of a CT to the cost of unserved energy ( e.g., well in excess of $1,000/MWh) under extreme conditions. 9

Third, unserved energy costs represent the value of lost load to customers. This value typically is derived from customer surveys.

Finally, capacity resource carrying costs are the costs of adding additional capacity in $/kW-yr.

The unserved energy costs are easily calculated in most reliability models. However, the production cost of expensive units, and the portion of reliability-related costs associated with power purchases during reliability and emergency events must be considered. SERVM utilizes a scarcity pricing model to simulate purchase costs during capacity shortages. For this case study, 10 years of actual historical prices from bilateral reliability and emergency purchases in the region were analyzed to estimate scarcity pricing curves which vary with reserve margin and the amount of capacity needed. SERVM was then calibrated to an actual historical year to ensure that the model is accurately projecting the cost of reliability purchases.

Lowest-Average-Cost Reserve Margin

Figure 1 shows one set of results from this case study. The figure shows the probability-weighted average cost of various reliability-related cost elements as a function of planning reserve margins. The lowest-average-cost reserve margin can be determined, for example, based on the point at which total reliability-related costs plus the cost of carrying additional reserves is the lowest, ignoring the uncertainty of costs around the weighted average costs shown in the chart. In the case study, this lowest-average-cost reserve margin is 12 percent. But this result will vary significantly across regions based on their size, load shape, resource mix, and many other factors.

The analysis also shows that, for the system studied here, the primary driver of reliability costs is expensive market purchases. In contrast, and contrary to usual reliability study assumptions, the value of lost load isn’t a highly significant factor in determining optimal reserve margins. Even if the value of lost load is changed by $5,000/MWh, the lowest-average-cost or risk-neutral optimal reserve margin shifts by only approximately