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Office equipment is expected to be the fastest-growing segment of commercial energy use over the next 20 years, yet many aspects of office equipment energy use are poorly understood. User behavior, such as turning off devices at night or enabling power management, influences energy use to a great extent. The computing environment also plays a role both in influencing user behavior and in the success of power management. Information about turn-off rates and power management rates for office equipment was collected through a series of after-hours audits in commercial buildings. Sixteen businesses were recruited, including offices (small, medium and large offices in a variety of industries), schools, and medical buildings in California, Georgia, and Pennsylvania. The types and power states of office equipment found in these buildings were recorded and analyzed. This article presents these data for computers, monitors, printers, copiers, fax machines, scanners and multi-function devices. These data can be used to improve estimates of both energy consumption for these devices and savings from energy conservation efforts.

This research was conducted in support of two branches of the EPA ENERGY STAR program, whose overall goal is to reduce, through voluntary market-based means, the amount of carbon dioxide emitted in the U.S. The primary objective was to collect data for the ENERGY STAR Office Equipment program on the after-hours power state of computers, monitors, printers, copiers, scanners, fax machines, and multi-function devices. We also collected data for the ENERGY STAR Commercial Buildings branch on the types and amounts of miscellaneous plug-load equipment, a significant and growing end use that is not usually accounted for by building energy managers. For most types of miscellaneous equipment, we also estimated typical unit energy consumption in order to estimate total energy consumption of the miscellaneous devices within our sample. This data set is the first of its kind that we know of, and is an important first step in characterizing miscellaneous plug loads in commercial buildings. The main purpose of this study is to supplement and update previous data we collected on the extent to which electronic office equipment is turned off or automatically enters a low power state when not in active use. In addition, it provides data on numbers and types of office equipment, and helps identify trends in office equipment usage patterns. These data improve our estimates of typical unit energy consumption and savings for each equipment type, and enables the ENERGY STAR Office Equipment program to focus future effort on products with the highest energy savings potential. This study expands our previous sample of office buildings in California and Washington DC to include education and health care facilities, and buildings in other states. We report data from sixteen commercial buildings in California, Georgia, and Pennsylvania: four education buildings, two medical buildings, two large offices (> 500 employees each), three medium offices (50-500 employees each), and five small business offices (< 50 employees each). Two buildings are in the San Francisco Bay are a of California, nine (including the five small businesses) are in Pittsburgh, Pennsylvania, and five are in Atlanta, Georgia.

This research was conducted in support of two branches of the EPA ENERGY STAR program, whose overall goal is to reduce, through voluntary market-based means, the amount of carbon dioxide emitted in the U.S. The primary objective was to collect data for the ENERGY STAR Office Equipment program on the after-hours power state of computers, monitors, printers, copiers, scanners, fax machines, and multi-function devices. We also collected data for the ENERGY STAR Commercial Buildings branch on the types and amounts of "miscellaneous" plug-load equipment, a significant and growing end use that is not usually accounted for by building energy managers. This data set is the first of its kind that we know of, and is an important first step in characterizing miscellaneous plug loads in commercial buildings. The main purpose of this study is to supplement and update previous data we collected on the extent to which electronic office equipment is turned off or automatically enters a low power state when not in active use. In addition, it provides data on numbers and types of office equipment, and helps identify trends in office equipment usage patterns. These data improve our estimates of typical unit energy consumption and savings for each equipment type, and enables the ENERGY STAR Office Equipment program to focus future effort on products with the highest energy savings potential. This study expands our previous sample of office buildings in California and Washington DC to include education and health care facilities, and buildings in other states. We report data from twelve commercial buildings in California, Georgia, and Pennsylvania: two health care buildings, two large offices (> 500 employees each), three medium offices (50-500 employees), four education buildings, and one "small office" that is actually an aggregate of five small businesses. Two buildings are in the San Francisco Bay area of California, five are in Pittsburgh, Pennsylvania, and five are in Atlanta, Georgia.

Since 1998, 817 motor efficiency test data sets, in the 1-500-hp (0.75-375 kW) range have been collected from several sources in different countries around the world, for 50 and 60 Hz. The test data include the motor efficiency using the IEC 34-2 and IEEE 112-B test standards, and the quantification of the stray load losses (SLLs), using the IEEE 112-B method. In 125 cases, the test data include the efficiency computed with both methods. The aim of this paper was the quantification of the discrepancy between the two mentioned standards, and to establish an approximate method to allow the comparison between motors tested with the two standards. Based on the significant number of collected motor data sets, it was concluded that, when compared to the IEEE 112-B standard, the IEC 34-2 standard is less accurate, and gives typically higher efficiency values, mainly because of the SLLs estimation procedure. The IEEE 112-B SLLs computed values are typically higher than the IEC SLLs predefined values, on average of 1.0 and 0.8 percentage points for 50-Hz and 60-Hz motors, respectively. Also, the average SLLs values vary slightly with the motor power. Using efficiency measurements made with both standards on the same motors, it was possible to confirm that the SLLs are the main reason for the observed discrepancy in the efficiency values. The results of the analysis carried out in this paper offer the possibility of comparing the efficiency of motors tested under the IEC 34-2 standard with motors tested with IEEE 112-B, leading to a choice of the most cost-effective option. This paper also provides a key contribution to the ongoing revision of the EEC 34-2 standard. Index Terms--Efficiency testing standards, induction motors, market transformation, motor testing, stray load losses.

In several states, public utility commissions have adopted surcharges for environmental externalities (adders) to be used in electric utility planning. The Massachusetts adder system applies major surcharges to emissions of sulfur dioxide, nitrogen oxides, and carbon dioxide. In this paper we explore the implications in terms of cost and emissions of using the Massachusetts adders as shadow prices in dispatching the pooled electric power system in New England. Our analysis has made use of a probabilistic production cost simulation model to estimate the impacts on the present system, and on a resource mix envisioned 15 years hence. The externality cost adders are used to influence the dispatch of a fixed configuration of power plants and not used to affect the composition of the future resource mix. Compared to conventional dispatch, emissions of SO2 and NOx drop by 10% to 15%, while carbon emissions remain virtually unaffected. The production cost penalty is 3% to 4%. In each year, reductions are accomplished mainly by shifting generation away from New England's coal steam power plants.

Incorporating demand-side resources into the planning regime of fast-growing electric utilities in developing countries is a particular challenge. A method is developed for valuing the contribution of conservation under these circumstances and illustrated through scenarios of electricity savings in Thailand's large commercial sector. The primary value of these scenarios is in the creation of opportunities to defer or cancel plants planned for future inclusion in the system. The benefits of such deferments are twofold: a direct reduction in capacity needs commensurate with the load impacts of the scenario, plus a reduction in the reserve margin required to maintain sYstem reliability. Comparison of the capital requirements of the conservation scenarios versus the deferrable plant capacity showed that conservation is substantially less capital intensive.