The best example of combined dynamic rates and smart billing is found in Ontario, Canada. It uses central MDM to produce time-differentiated customer bills.
Directly Controlling the Winter Peak
Learning lessons from PSE’s residential demand response pilot.
Residential direct load control programs intended to reduce peak residential demand on hot summer afternoons have become increasingly common, particularly in more innovative jurisdictions such as Arizona and California. In the last two years, dozens of evaluations of air-conditioning direct load control pilots and programs have been published, and as a result, a fairly solid understanding of potential demand reductions exists. Likewise, the effects and persistence of so-called “snapback”—the increase in demand above normal levels immediately following a curtailment event—are also well understood.
Meanwhile, utilities in winter-peaking areas have received far less attention. Although a small number of studies examining the impact of water-heater direct load control during the winter do exist, robust empirical studies examining the impacts of the direct load control of space heating in winter aren’t nearly as common. Thus, Navigant’s recent evaluation of Puget Sound Energy’s (PSE) residential demand response (DR) pilot and survey data reported by Navigant contractor Energy Market Innovations should be of particular interest to winter-peaking utilities.
Direct Load Control at PSE
The residential DR pilot was a direct load control program running from October 2009 through September 2011, during which time participants’ water heating or space heating—or both—were cycled down on seven winter mornings and two winter afternoons. Afternoon events occurred on days that also had morning events. “Cycling” refers to the strategy by which devices are controlled—for example, a 50-percent cycling strategy is when the controlled device is allowed to operate only half the time it would normally operate during a given half-hour and a 100-percent cycling strategy simply means the controlled device was completely shut off during the period of the event. On the pilot event days, water heater cycling was 100 percent, while space heating cycling was 50 percent, with an adaptive algorithm.
The pilot was conducted in Washington State on Bainbridge Island, in the western portion of the PSE service area. Natural gas service is unavailable on the island, and nearly all of the homes rely on electric space and water heating. The population of the island has increased from approximately 12,000 in 1980 to more than 23,000 in 2010, and the island’s substations are under considerable strain when winter demand peaks.
More than 500 participants participated in the pilot—electing to allow PSE to control their water heaters, space heaters, or both. Figure 1 shows the distribution of controlled devices among pilot participants. Of the 528 participants, quarter-hourly interval data were available for 494. Device-connected data loggers weren’t used in this analysis, meaning that the analysis relied on whole-home, rather than device-specific, demand data.
Curtailment was controlled via broadband using two-way communication, allowing PSE’s implementation vendor to track signal failures. Thus, Navigant was able to exclude devices experiencing signal failure from its analysis.
Program Demand Impacts
Demand reduction and snapback impacts were estimated using an econometric technique known as “fixed effects,” which is frequently used for impact