Low energy prices have weakened the business case for advanced metering. Regaining momentum might depend on innovation to strengthen the benefits.
Learning from California's QF Auction
Both a Winner and Loser
A QF bid a 274-MW project against an IDR with the same effective capacity:
Energy-related Capacity Cost:
Peak Shortage Cost:
Energy Cost: (›/Kwh) 0
The QF was tentatively selected as a winner for its IDR. However, some smaller bidders won a share of the IDR capacity by posting lower scores. As a result, the capacity block won by the large QF was downsized to 271.6 MW. A small part of its bid (2.4 MW) lost in the auction. Consequently, it was also the first losing bid for the IDR under the California QF auction rules. That means that its winning bid inadvertently set the auction price. Thus, for the 271.6 MW that won, the QF would be paid exactly what it bid and would receive no second-price premium. It would receive payments of approximately $59.44 million per year in 1998 dollars.
If the QF's bid has actually represented its true costs, these yearly payments will cover its costs but no more.
Suppose instead that this QF had increased the energy-related capacity cost (ERCC) component of its bid. By so doing, the QF would have also increased its own winning bid and, coincidentally, also the first losing bid score. Consequently, the payments to all winning QFs would have risen, including the payment for the 271.6-MW block that this QF won. For each $1 per kilowatt-year increase in the ERCC, this QF would have raised its capacity payments by $271,600 per year. That's pure profit. This strategy would risk losing the bid, but might prove worth it in the long run.
FIXING THE HOLES
If a QF auction is meant to elicit a particular high-level behavior from the participants, the designer may have to compromise in choosing a model.
Several parties recommended developing the QF auction by extending a first-price auction. They argued that a first-price auction format was easier to extend to complex products such as the capacity and energy being offered by the QFs. But the CPUC rejected this approach, assuming that the resulting auction would not exhibit the desired uniform pricing and true-cost-revealing characteristics. While the CPUC succeeded in achieving an auction with a strong uniform-pricing characteristic, the results show less success in achieving the true-cost attribute. Of course, an auction with both these properties could have been designed, but only by using an alternate view of a simple second-price auction as our model.
Here is an alternate definition of a simple second-price auction:
s Select N winning bids to minimize the sum of the costs of the winning bids.
s Pay each winning bidder the most that he could have bid and remain a winner.
In this alternate approach, the utility selects winners from among the QFs and IDRs, consistent with regulatory constraints, to maximize the capacity and energy benefits provided by the winning QFs and IDRs (after subtracting the capacity and energy costs of the winning QFs and IDRs, and the transmission costs borne by the utility). The data required under this approach includes the same type of data used