An increasing amount of electricity is used by equipment that is neither fully "on" nor fully "off." We call these equipment states low power modes, or "lopomos." "Standby" and "sleep" are the most familiar lopomos, but some new products already have many modes. Lopomos are becoming common in household appliances, safety equipment, and miscellaneous products. Ross and Meier (2000) reports that several international studies have found standby power to be as much as 10 percent of residential energy consumption. Lopomo energy consumption is likely to continue growing rapidly as products with lopomos that use significant amounts of energy penetrate the market. Other sectors such as commercial buildings and industry also have lopomo energy use, perhaps totaling more in aggregate than that of households, but no comprehensive measurements have been made. In this paper, we propose a research agenda for study of lopomo energy consumption. This agenda has been developed with input from over 200 interested parties. Overall, there is consensus that lopomo energy consumption is an important area for research. Many see this as a critical time for addressing lopomo issues. As equipment designs move from the binary "on/off" paradigm to one that encompasses multiple power modes, there is a unique opportunity to address the issue of low power mode energy consumption while technology development paths are still flexible.

The United States has labeled appliances with the EnergyGuide labels since 1980. Consensus is growing that this label is confusing to consumers and has little impact on purchase decisions. Many researchers have documented that alternative labeling approaches are effective in other countries. The authors comprehensively evaluated the U.S. appliance labeling program for white goods, heating and cooling equipment, and water heaters, with emphasis on products sold through retail outlets. To date, our research has included consumer focus groups and semi-structured interviews with various market actors to assess how best to communicate energy information. With consumers and retail sales staff, five graphical designs were tested a European-style, letter based graphic; an Australian-style star-based graphic; a speedometer-style graphic; a thermometer-style graphic; and the current U.S. style. With manufacturers and contractors, we did not directly test alternate designs. Instead, we asked their opinion of and experience with the current EnergyGuide labeling program.

The crisis atmosphere surrounding electricity availability in California during the summer of 2001 produced two distinct phenomena in commercial energy consumption decision-making: desires to guarantee energy availability while blackouts were still widely anticipated, and desires to avoid or mitigate significant price increases when higher commercial electricity tariffs took effect. The climate of increased consideration of these factors seems to have led, in some cases, to greater willingness on the part of business decision-makers to consider highly innovative technologies. This paper examines three case studies of innovative technology adoption: retrofit of time-and-temperature signs on an office building; installation of fuel cells to supply power, heating, and cooling to the same building; and installation of a gas-fired heat pump at a microbrewery. We examine the decision process that led to adoption of these technologies. In each case, specific constraints had made more conventional energy-efficient technologies inapplicable. We examine how these barriers to technology adoption developed over time, how the California energy decision-making climate combined with the characteristics of these innovative technologies to overcome the barriers, and what the implications of hurdling these barriers are for future energy decisions within the firms.

This paper presents the results of 11 after-hours walk-throughs of offices in the San Francisco CA and Washington D.C. areas. The primary purpose of these walk-throughs was to collect data on turn-off rates for various types of office equipment (computers, monitors, printers, fax machines, copiers, and multifunction products). Each piece of equipment observed was recorded and its power status noted (e.g. on, off, low power). Whenever possible, we also recorded whether power management was enabled on the equipment. The floor area audited was recorded as well, which allowed us to calculate equipment densities. We found that only 44 percent of computers, 32 percent of monitors, and 25 percent of printers were turned off at night. Based on our observations we estimate success rates of 56 percent for monitor power management and 96 percent for enabling of power management on printers.