| Popis: |
Approximately 70 percent of industrial electricity is used to power electric motors. Recent studies show that there is still tremendous energy-saving potential in converting to new, higher efficiency motors. The objective of this project was to provide fact-based information that has the potential to significantly affect motor choices in U.S. industry. The methodology of this project was to conduct analysis and testing in two areas: energy efficiency of inservice motors and the reliability of new versus repaired motors. The project involved partners from four states: California, New York, North Carolina and Washington. Advanced Energy, the primary proposer, has been a leader in the motor industry for more than 20 years and operates the only independent, NIST-accredited motor test laboratory in the United States. The Washington State University Energy Program has also been a leader in the motor industry for more than a decade. Project partners also include the California Energy Commission and the New York State Energy Research and Development Authority (NYSERDA). Strong support came from a number of motor manufacturers, who have provided in-kind support exceeding 40 percent of the total project cost. The project also has had the support of a wide range of other parties, including the National Electrical Manufacturers Association (NEMA), the Consortium for Energy Efficiency (CEE) and its Motor Decisions Matter campaign, the Copper Development Association and the American Council for an Energy Efficient Economy (ACEEE). This project has provided the first fact-based information for estimating motor efficiency in older motor populations. It verified that many of the assumptions are reasonably accurate and should continue to be used. It also demonstrated that motor reliability should be more strongly considered in the repair versus replace decision, but points out that data to support these decisions is extremely weak. One of the major recommendations is that motor users and industry advocates should be doing a better job of collecting data on motor reliability (the mean time between failures) of their motor populations. |
