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Using Hourly System Lambda to Gauge Bulk-power Prices
and is now available to the public via electronic bulletin board.
System lambda is closely associated with the marginal cost of producing electricity and offers a good indicator of the competitive price for electrical energy. System lambda is a product of control area economic dispatch. Certain plant owners are accustomed to tracking the changing level of customer demand. Each of these dispatchable plants exhibits its own production cost curve, which identifies variable costs (mostly incremental fuel cost) at each level of output. The system lambda represents the variable cost of the last kilowatt produced over a particular hour. The plants most closely following load tend to be utility units with higher variable operating costs (see Figure 1). That's intuitive; you want to use the power plants with the lowest variable costs as much as possible.
Electricity demand can fluctuate widely, between hours, days, and seasons. In general, system lambda correlates with load levels (see Figure 2).1 Utilities with high cost generators can be expected generally to carry higher system lambdas. Thus, for example, utilities with mostly oil and gas power plants show higher average system lambdas than utilities that operate low-cost coal plants.
A Look at the FERC Data
Some of the newly available FERC system lambda data are shown for contiguous regions in the eastern United States (see Figure 3). This data shows the 1993 annual average (that is, an average over 8,760 hours of data). For 1993 the average lambda for the PJM power pool was nearly 22 mills (2.2 cents) per kilowatt-hour (Kwh).2 In contrast, the average system lambda is only 15 mills (1.5 cents) per Kwh for two leading utilities (American Electric Power and Allegheny Power System) located in the North American Electric Reliability Council Region (NERC) known as the East Central Area Agreement (ECAR). These companies own many power plants located close to the Appalachian coal fields to the west of PJM. The ECAR region is directly interconnected with PJM. Utility average system lambda data are also presented for some utilities to the north and south of PJM.
Several factors (among many) explain differences between PJM and ECAR utilities: 1) the generating fuel mix, 2) economy interchanges, and 3) transmission bottlenecks.
In 1993, PJM oil and gas generation was 5 percent of total mix. In contrast, in ECAR, oil and gas accounted for less than one percent of utility generation. A higher PJM cost seems logical. Also, sales of economy power from ECAR to PJM would yield cost savings. Both sides would benefit. The availability of low-cost ECAR power means that PJM's incremental sources of power come from ECAR utilities. In this respect, the large differential in average annual lambda is at first glance surprising. However, consider that high-voltage transmission interties between PJM and ECAR are heavily loaded. In actuality, this link is one of the most used inter-NERC regional interties in the country. Trades that would decrease the lambda difference may not be possible due to lack of transmission capacity.
Of course, differences in computational methods do place certain limitations on the FERC data. The FERC