Currently, for most consumers, the price of electricity does not reflect the fluctuations in production costs throughout the day as the demand for electricity changes. Electricity generated at peak periods (such as weekday afternoons, summers, and times of shortage) is generally more expensive to produce than electricity generated at off-peak times. This is because peak periods may require the use of generators that are infrequently used or inefficient compared with other power plants. Nevertheless, most consumers pay a fixed price per unit of electricity used. It is desirable to reduce electricity consumption during high-cost production times, but consumers often have little incentive to do so.
“Demand response” refers to programs or prices designed to encourage consumers to reduce electricity usage, especially during times of peak demand, in response to a price signal. There are two types of demand response: incentive-based and price-based. With incentive-based demand response, participants lower their power usage because of a positive inducement or incentive. For example, large customers, such as manufacturers, might be offered payment to reduce usage. Direct-load control is another incentive-based demand response model. Under this type of program, the customer agrees to let the utility control a major appliance, such as an air conditioner, electric water heater, or pool pump. At times of peak demand, the utility could briefly turn off the designated appliance to avoid a surge in power demand. Customers can volunteer to participate in direct-load control programs, and in some cases the customer might receive a bill credit for participation. In most programs, the customer can override the utility’s control of the appliance.
Under a price-based demand-response model such as time varying rates, retail customers receive price signals, with the expectation that higher prices will induce a cut back in consumption. Some utility companies have proposed using smart meters to enable them to charge different prices for electricity based on when the consumer uses it. Utility companies seek to implement smart meters to create a demand response, encouraging consumers to shift some of their electricity usage from higher-cost peak times to lower-cost off-peak times. If smart meters decrease electricity use during peak periods, utility companies contend, consumers will realize substantial savings. Utilities also claim that less system stress during high-demand times would lead to fewer equipment failures and thus fewer blackouts. In addition, they predict that customer service would improve.
Some people have voiced concern that the use of smart meters would benefit high-income and high-usage customers but could lead to higher costs for customers who have limited options for reducing their demand to off-peak times, such as lower usage customers and seniors. In that case, smart meters might achieve their overall goal of reducing peak demand, but at the expense of some users.
Time-Varying Rates and Demand Response: Policy
Time-varying rates ad demand response
Policymakers should prohibit any time-of-use metering and billing program that is likely to have an adverse impact on residential customers generally or that shifts costs to those who use less than the average amount of electricity.
Policymakers should ensure that all time-of-use metering and billing programs adopt an opt-in approach.
Policymakers should prohibit mandatory or opt-out time-of-use metering and billing programs.
Policymakers should ensure that any time-of-use metering and billing program is accompanied by a consumer education program.
Policymakers should ensure that any time-of-use (or related rate design) pilot program for residential customers includes and identifies customers with low incomes and measures the program’s impact on customers who do not or cannot take actions to avoid the higher peak-time prices.
For states considering the installation of advanced or prepaid meters, policymakers should order a thorough analysis of such an effort and conduct contested proceedings to determine the costs and benefits to lower-income customers, customers at different usage levels and with different usage patterns, and residential customers in general.