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.
across the continent. In most cases, published analyses focus on the behavior of the average customer. However, the databases are a fertile source of empirical information on customer response to rates that can be harnessed to test—and resolve— some of these distributional impacts that continue to be debated ad nauseum . The experimental data differ from the myriad datasets generated as part of ongoing load-research activities such as cost-of-service studies, load forecasting, and direct access compliance. Those datasets include information on hourly (and half-hourly) load shapes on a representative sample of customers. They usually don’t include information on customer characteristics (such as size and type of dwelling, saturation of end uses, and sociodemographic factors) nor do they include information on customer price responsiveness, both of which are richly represented in the experimental datasets.
• Facilitate customer choice : One of the objectives of power market restructuring activities initiated in the mid-1990s was to provide more choices to customers. Initially, policymakers thought the best way to accomplish this goal was by providing choice of power supplier. They hoped competitive power suppliers also would provide choice of pricing products and services to customers. The former avenue has not been found to work for mass market customers—at least not in California, the largest state to attempt customer choice. Even in places such as Baltimore and the District of Columbia, customer-switching rates for mass-market customers are very low. Thus, a way must be found for pursuing the latter through the incumbent utility provider. This is not as difficult as it seems. The incumbent provider can design and market a variety of pricing products for customers. These would be differentiated along the risk-sharing spectrum and represent different ways of allocating risks between customers and suppliers. A middle-of-the-road option, such as critical-peak pricing, can be made the default option, and customers would have the option to switch over to any of the other options that better match their risk-taking preferences.
• Clearly and simply communicate prices and costs : Retail rate structures vary widely from state to state, with some vastly more complex than others. California’s residential electricity tariffs, for example, with their increasing block structure, subsidies and surcharges, and unbundled cost structure, are among the most convoluted tariffs in the continent. And that’s before California’s landmark pricing experiment, the Statewide Pricing Pilot (SPP), incorporated time-varying surcharges, credits and dynamic price variation. 5
Indeed, research conducted during the SPP indicated that many customers didn’t understand even the basic characteristics of their standard rates, let alone the nuances of how average and marginal prices move across rate tiers and time periods. On the other hand, the SPP showed that many customers did understand that prices were much higher during peak periods on critical days. Also, the SPP showed that time-varying prices can produce considerable peak demand reductions, even in a world of significantly increasing block tariffs and rate complexity. In other words, the SPP showed that even complex rates can produce demand response. What the SPP didn’t show, however, is whether significantly greater reductions could be achieved if rates