During the 1990s, electricity demand in the United States grew faster than did new generating supplies as a combination of stringent environmental laws, red tape, and greater environmental awareness slowed the construction of new power plants. Partial deregulation only made matters worse in places like California by leaving utilities stuck between deregulated wholesale power prices that are both high and volatile and retail rates that remain fixed. (1) As a result, many utilities sometimes pay upstream generators more for electricity than they can charge the public when they resell it. The problem came to a head in California last spring--bankrupting one of the state's three main utilities and pushing a second to the very verge of bankruptcy--and it could also strike elsewhere.
To complete the deregulation of the power industry and to avoid another California-style crunch, regulators must now link electricity prices in retail and wholesale markets. The most feasible way to do so would be time-of-use, or "dynamic" pricing, which allows utilities to pass on to consumers at least part of the price variation occurring within a given day, thus damping demand when supplies are tightest (and prices are highest). To put it simply, customers should pay more for power used at noon than at midnight, much as long-distance telephone rates vary according to the time and the day of the week.
Because electricity cannot be stored in large quantities, inefficient peak-generating capacity must be fired up when demand is highest. Electricity produced in this way is very expensive, and wholesale prices are therefore volatile, even in markets with ample generating reserves. On the Pennsylvania, New Jersey, and Maryland power grid, for instance, wholesale prices in 2000 ranged from a low of $10 a megawatt-hour to a high of $800, even though the area has generating reserve margins of almost 20 percent (Exhibit 1). (2)
Once exposed to electricity prices that vary during the day, consumers are likely to alter their consumption patterns, especially during the critical peak periods. Some people will choose to run their dishwashers at night instead of after breakfast, for instance, while others will reduce their total energy consumption during peak-demand periods by using less air-conditioning or turning off a few lights. Experiments with dynamic pricing in Texas have shown that consumers shifted or curtailed almost a third of their demand during peak periods. We estimate that by moving just 5 to 8 percent of energy consumption to off-peak hours and cutting an extra 4 to 7 percent of peak demand altogether, utilities, consumers, and businesses could realize savings of as much as $15 billion a year.
Despite this potential, utilities are reluctant to invest in the technology needed to implement dynamic pricing for the mass market, in part because they are unsure whether state regulatory commissions, which set the retail rates for almost all customers, will allow rates to vary by time. Even if such rates are approved, huge up-front expenditures will be required to retrofit or replace household meters, to develop the means of collecting the data, and to calculate more complicated bills. A utility must therefore receive some assurance from regulators that it will be able to recoup these costs and make a return on the investment.
Is the cost justified? We believe that it is. Real-time metering will create an enormous opportunity for utilities and other players in the power industry. It will enable utilities--particularly those that rely most on upstream generators--to capture savings from lower peak prices and to mitigate a main source of business risk. It will also create an array of new business opportunities. The metering technology needed for dynamic pricing generates valuable information about consumer demand and will make it possible for power marketers to offer new pricing and service options. Some companies might offer consumers risk-management products to remove price risk arising within a given day, for example; others might conduct home audits to find ways of cutting peak demand. …