Although today microgrids serve a tiny fraction of the market, that share will grow as costs fall. Utilities can benefit if they plan ahead.
Transition to Dynamic Pricing
A step-by-step approach to intelligent rate design.
setting prices so they vary across customer classes or segments in accordance with variation in the cost of supply to those classes or segments. An example is having higher average prices for households with central air conditioning, or time-varying prices that incorporate the higher cost of supply associated with air conditioning loads during peak periods. Equity in this context focuses on eliminating cross-subsidies that are inherent in average cost pricing.
According to the second definition, lifeline rates (based on the theory that low-income consumers are low users) and such explicit discounts as the CARE tariff are worthy of pursuit. Lifeline rates (sometimes called baseline rates) are designed to meet the critical or lifeline needs of all consumers by supplying power at subsidized rates for the first several hundred kilowatt hours of usage. They serve a laudable social goal but detract from the overriding goal of economic efficiency. Regulators considering such rate designs should quantify the loss in economic efficiency they will create.
For example, suppose the full cost of power is 10 cents per kWh and customers pay 7 cents/kWh on the first 300 kWh of usage that’s designated as lifeline usage. Customers are getting a price subsidy of 3 cents/kWh on 300 kWh, or $9. In the second step, the $9 subsidy would be converted into an income subsidy and the price on the first 300 kWh would be raised to its full marginal cost of 10 cents/kWh. Probably most consumers would spend a good portion of the $9 income subsidy on higher value necessities such as food, clothing and transportation and conserve a certain amount of electricity by turning off lights in occupied rooms, perhaps installing compact fluorescent lamps, weatherizing their homes, adjusting their thermostat settings, and so on. The amount of electric usage might come down by a few percentage points, which would promote the state’s goal of enhancing energy efficiency.
In addition, removing price subsidies would improve the financial position of the electric utility. The financial burden of subsidizing customers would be shifted back to state and federal governments, on whose shoulders ultimately it should rest.
This social goal could be achieved, without compromising the goal of basing prices on costs to achieve economic efficiency in the allocation of scarce resources, by expanding the federal government’s Low Income Home Energy Assistance Program (LIHEAP).
Commissions need to test hypotheses about the distributional impacts of various rate options on different customer segments, rather than basing them on supposition and conjecture. For example, do low-use customers have flatter load shapes than high-use customers? If so, they are likely to be made better off with TOU pricing and not worse off, as some consumer groups often contend. Many myths and preconceptions have grown around equity issues. The only way to slay the myths is to quantify and analyze the implicit hypotheses concerning which tariff will make which customer group worse off.
Fortunately, new databases now exist that quantify the response of customers to alternative rate designs, making such analysis possible. A good example is the individual customer data generated by dynamic-pricing experiments