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. Eventually, power retailers could offer a range of pricing plans similar to those of long-distance and mobile-phone service providers. Moreover, as retail electricity markets become more competitive, real-time metering will permit power providers to differentiate themselves.

All told, the implementation of the platform for dynamic pricing will create business opportunities worth $25 billion to $30 billion

Companies outside the power industry should also take note of the opportunities. With about 100 million residential and small-business meters to be retrofitted or replaced, technology manufacturers have a large market to address. Wireless and other kinds of telecommunications infrastructures will be needed to transmit the reams of data from each meter back to the utility, and software will be required for everything from data storage on meters to new billing systems. All told, the implementation of the platform needed for dynamic pricing will create business opportunities worth from $25 billion to $30 billion.

Making it happen

The first step in moving from today’s once-a-month meter readings to a more detailed record of household electricity consumption involves upgrading meters to track customers’ usage by the hour or the quarter hour. Time-of-use meters and chipsets are now available commercially, and existing meters can be upgraded at a cost per meter of from $80 (for a retrofit) to $200 (for a complete replacement).

Retrieving a whole dataset of hourly usage (rather than a single number) from each household will make automated meter reading (AMR) essential for utilities. First-generation AMR technology used a radio-frequency transmitter on each meter to send data in short bursts to a roaming receiver truck, which then downloaded the data back at the utility. The second generation of technology, now available, uses 900-megahertz transmitters, cellular transmitters, or both to send data directly to the utility. We estimate that a fixed wireless system using these networks would involve a onetime investment of $220 to $320 a household, with monthly operating expenses of $3 to $4 a meter, including billing.

A more recent innovation might also be feasible. Power-line-carrier (PLC) technology enables electricity grids, like telephone grids, to carry signals in and out of homes. Technical barriers have limited PLC’s promise of bringing broadband services to them, but the grid could certainly handle the relatively narrow bandwidth needed to send data from electricity meters back to data collection boxes shared by several neighboring customers. From there, the data can be sent to the utility by various means, including fixed wireless or wireline communications. We estimate that this approach would require a more modest investment, of $160 to $170 per household—again with monthly operating expenses of $3 to $4.

In addition, a utility will need to upgrade its customer information system (CIS) to handle the increased data flow and flexible rate structures. The typical utility CIS is a rickety patchwork operation that has evolved over 20 or more years. For a midsize or large utility, the cost of replacement would be $50 million to $100 million, and many systems will soon be due for upgrading or replacement anyway. All energy service providers, regardless of their retail-pricing structure, will have to assess whether their current systems can deliver the level of service that their customers expect, including the provision of more flexible pricing programs.

Once the infrastructure is in place, retail customers can be offered several pricing options. The simplest is to set fixed peak and off-peak rates that can be changed seasonally. More sophisticated systems might set several different rates during the day or the hour (real-time pricing), with the tariffs published in advance and available on the Internet or over the telephone.

The money on the table

Dynamic pricing has already been implemented on a limited basis, with promising results. The leader in this area is Georgia Power, which introduced meters that record hourly usage for large industrial users in 1992. Today about 1,650 businesses use such meters. The peak-time demand of these customers, which pay rates that vary hourly according to wholesale market prices and are posted on the Internet, is reported to have dropped by 17 percent since the meters were adopted.³ Peak wholesale prices have fallen accordingly, benefiting all of Georgia Power’s customers and the utility itself. Amoco Fabrics and Fibers, for example, has shaved 10 percent, or $800,000, off its annual power bill by stopping operations during price peaks, without affecting turnover.⁴

In Washington State, Puget Sound Energy (PSE) is experimenting with variable pricing for small businesses and home owners. In 2001, state regulators approved a five-month pilot plan to introduce peak and off-peak rates for 300,000 home owners and small-business customers. Under the company’s Personal Energy Management program, customers paid about 12 percent less during off-peak hours and 17 percent more during peak hours (Exhibit 2). Wireless devices on the customers’ meters tracked hourly usage and transmitted data back to PSE’s operations center once a day using fixed wireless technology. Customers could track their energy usage themselves on the company’s World Wide Web site.

Besides reducing both PSE’s exposure to soaring prices in the wholesale market and the need to ask regulators for rate increases, the program has improved customer service and promoted conservation in a territory with an environmentally conscious population. The results showed that consumers responded to variable energy pricing: within two months, they had shifted 5 percent of peak electricity consumption to off-peak periods.⁵ PSE’s program also indicated that moving from flat to variable rates leaves the average customer’s bill unchanged if the consumption pattern remains the same and actually cuts the bill if the load shifts away from high-priced periods. At the time of writing, regulators were considering whether to allow the scheme to be made permanent.

As already noted, our analysis indicates that the cost of introducing dynamic pricing for all mass-market customers around the country—a cost that includes meters, the necessary communications infrastructure, and back-office systems—would be $25 billion to $30 billion in all, with maintenance and operating costs of $7 billion to $8 billion a year. If peak demand were to fall nationwide by 5 percent, as local peak demand did when PSE ran its pilot program, savings of up to $15 billion a year could be expected (Exhibit 3). Some $3 billion of this sum would be saved by customers as they shifted consumption away from peak periods; the rest would come from falling wholesale electricity prices as peak demand dropped. Thus, the benefits of dynamic pricing could easily outweigh the costs of implementing it—if regulators allowed utilities to keep some of the cost savings. Even at the level of individual households, where energy bills are relatively small, utilities would be able to make attractive returns on their investment if they were permitted to build its cost into their rate base. According to our analysis, the investment will generate a positive net present value for electricity customers, thus satisfying one of the regulators’ prime objectives (Exhibit 4).

Dynamic pricing can bring other benefits as well. We estimate that peak energy demand could be cut by at least 30,000 megawatts nationally—enough to avoid (or at least delay) the construction of as many as 250 peak-generating plants, to prevent the burning of 680 billion cubic feet of gas a year, and to eliminate 31,000 tons of NOx (nitrogen oxides) emissions.

The electricity market of the future

Price-responsive demand removes one of the principal risks of the business of retailing electricity

Dynamic pricing is important for reasons beyond the purely financial gains from less volatile wholesale prices. Price-responsive demand helps mitigate spikes in wholesale market prices—spikes that utilities may or, as in California, may not be allowed to recoup. It thus eliminates one of the main risks of the retail-electricity business and makes risk management easier.

More significant, the advanced metering capabilities and communications platform needed for dynamic pricing will lay the foundation for the next generation of energy services. And that future may not be far away. Enel, the giant Italian utility, is staking its claim on home networks by deploying 27 million advanced meters and associated communications devices within its territory. The system, to be rolled out over three years by the California-based company Echelon, will initially come into use for automated meter reading, dynamic pricing, and the remote connection (and disconnection) of services. Eventually, Enel and Echelon expect the metering and communications platform to deliver services such as home security and the remote monitoring of domestic appliances (which would make it possible for a utility to tell when an appliance was malfunctioning or aging, since it would use more electricity if it was).

The services Enel and Echelon envision are just the tip of the iceberg. Ultimately, energy-management systems embedded in home networks may be able to receive continuous load-control signals from the power provider and to adjust electricity usage accordingly—raising or lowering the temperature of central heating, for example, or instructing washing machines to turn themselves on when prices were lower. Such systems would also enable customers to control their appliances remotely or allow preprogrammed software to make relatively painless conservation decisions for them. Decisions about when to turn on the heating, say, could be made on the basis of prices and weather forecasts. Moreover, by integrating home security features into the same basic control center, home owners could give repair workers and other service personnel access, by remote control, to specific rooms in houses. Indeed, an energy control platform may be just the "killer application" home networks need to spark consumer demand.⁶ The fact that power providers are trusted with access to the home puts them in a unique position to help roll out such networks.

All of these services provide the industry with new, higher-margin customer services. To pursue them, however, utilities will have to take the first step and strengthen the connection with their customers through real-time metering.

Only a few years ago, dynamic pricing for household electricity was just another nice economic theory. Today, new chip and wireless technologies make it feasible to roll out dynamic pricing on a large scale. In addition to generating big savings for customers and completing the restructuring of the energy industry, the technological platform needed will lay the foundation for the next generation of energy services. An enormous business opportunity is at hand. It is time for utilities, regulators, and other industry participants to seize it.