REAL-TIME PRICING OF ELECTRICITY FOR RESIDENTIAL CUSTOMERS - ECONOMETRIC-ANALYSIS OF AN EXPERIMENT

Under real-time pricing, a network operator sets the price level for a period according to a predefined scheme which depends on the state of demand and costs, and announces this price shortly before the period begins. The French state-owned electric utility experimented with a si x-rate real-time tariff, which divides the year into three types of da ys and each day into two periods. The number of days of each type is k nown in advance to the consumer, but the type of any particular day is announced only at the end of the preceding day. In order to evaluate the responsiveness of customers to this pricing option, we estimate th e Frisch demand functions for daily electricity consumption, derived f rom a simple dynamic model based on an additively separable intertempo ral utility function. As the marginal utility of expenditure which ent ers the Frisch demands follows a known stochastic process, the econome tric model has a state-space representation. We can then apply the Kal man filter to compute the log-likelihood function associated with each consumer's time series of electricity consumption. The main result of the analysis is that the real-time tariff improves the welfare of a m ajority of consumers participating in the experiment.