By unbundling usage from access, utilities can maximize contribution to margin and yet still retain load.
With deregulation and industry restructuring, energy utilities face price...
charges would be based on the marginal cost of transportation, instead of the marginal cost of the bundled service. Also, the optional tariffs must be designed so that the customer prefers it to the base tariff and to any other unbundled transportation service. Also, the customer must prefer the bundled service (transportation plus generation for electricity or transportation plus procurement for gas) to available competitive alternatives.
The design of optional tariffs for rebundled services is much more complex for two reasons. First, the number of possible combinations that must be analyzed is much greater. For example, for three services, the number of possible combinations of bundled, unbundled and rebundled services is eight (23 = 8), although not all combinations are expected to be offered. Second, when designing optional tariffs for rebundled services, it is necessary to estimate own-price elasticities and marginal costs for each unbundled service, and cross-price elasticities (to reflect the complement and substitute nature of the services) for each possible pair of services. Estimating own-price and cross-price elasticities for unbundled services is expected to be very complex. Moreover, utilities will have little or no data to estimate these parameters, because most of these services have not been offered.
One solution to this problem is to use contingent valuation methods to estimate customer response to hypothetical offerings. Such an approach has been used to assess the value that customers place on reliability, and to estimate the demand for new products.
The Benefits: A Case Study
This section illustrates the design of optional tariffs based on a random sample of 75 large industrial customers (peak demands in excess of 2 MW). The sample is from an electric utility that was experiencing considerable load loss due to self-generation and cogeneration. The price elasticity and marginal cost estimates used in the example are shown in Table 1.
The analysis is based on price elasticity estimates that are deliberately low and marginal cost estimates that are set deliberately high. Conservative estimates of price elasticities and marginal costs are used to ensure the actual results will be at least as favorable as those shown in the analysis.
Of the 75 customers, 10 have peak demand greater than 10 MW and a load factor greater than 50 percent. These customers are considered in danger of bypass from either self-generation or cogeneration. The remaining 65 customers are not considered at risk. Data on the margin recovery for all 75 customers are shown in Table 2.
For the purpose of designing competitive tariffs, the 10 customers considered vulnerable to bypass have been separated into four market segments based on size and load factor. This segmentation is used, because the costs of the competitive alternatives depend on these factors. The distribution of the at-risk customers is shown in Table 3.
The first step in the analysis is to determine if the utility is in danger of bypass. Table 4 provides the average price of utility service compared to that of the competitive alternatives for each of the four market segments.
As shown, the average utility rate exceeds the price of