New and affordable technology for providing detailed feedback on household electricity usage presents a host of opportunities for utilities and policy-makers to manage demand. This dissertation examines ways to use these devices to reduce - and shift the timing of - energy use in the residential sector by influencing consumers' behavior. The first portion of the study analyzes the impact of programmable thermostats (PTs) on energy use, focusing on residents' knowledge of climate control settings in the dwelling. I found that of households with natural gas heating systems, young households with PTs used 17 percent less heating energy on average. In addition, residents who did not know their thermostat settings tended to use 10 percent more energy for heating.

The main portion of the dissertation focuses specifically on the potential for better feedback on electricity usage to reduce household energy consumption. The existing literature suggests that feedback can reduce electricity consumption in homes by 5 to 20 percent, but that significant uncertainties remain in our knowledge of the effectiveness of feedback. These uncertainties include the variation in feedback effectiveness between demographic groups and consumers in different climate regions. This analysis uses these uncertainties to perform an exploratory analysis to determine the conditions under which the benefits of feedback outweigh the costs and to compare the cost-effectiveness of providing feedback against that of other DSM programs. I found that benefits would likely outweigh costs for enhanced monthly billing and real-time feedback and that cost-effectiveness was superior to that of other DSM programs for these types of feedback. For feedback that is disaggregated by appliance type, cost effectiveness was competitive with other DSM programs under a limited set of cases.

This study also examines how energy consumption devices should display feedback on GHG emissions from electricity use under a real-time pricing program. I found that load-shifting can cause GHG emissions to increase or decrease depending on region and season and in no discernable pattern. Therefore, feedback may be more useful and comprehensible to households in the form of total GHG emissions attributable to electricity usage instead of the emission rate of the marginal power plant. Finally, this dissertation explores ways to maximize the effect of feedback by evaluating which appliances may be best suited for appliance-specific feedback. Due to the energy use and behavioral factors associated with each appliance, the most promising appliances were those that heat water for taps, showers, hot tubs, and waterbeds.