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Wireless Sensor for Measuring Pump Efficiency [electronic resource] : Small Business Voucher Project with KCF Technologies

Published:
Washington, D.C. : United States. Dept. of Energy. Office of Energy Efficiency and Renewable Energy, 2017.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy
Additional Creators:
Oak Ridge National Laboratory, United States. Department of Energy. Office of Energy Efficiency and Renewable Energy, and United States. Department of Energy. Office of Scientific and Technical Information
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Summary:
This document is to fulfill the final report requirements for the Small Business Voucher (SBV) CRADA project with ORNL and KCF Technologies (CRADA/NFE-16-06133). Pumping systems account for nearly 20% of the world’s electrical energy demand and range from 25-50% of the energy usage in many industrial and building power plants. The energy cost is the largest element in the total cost of owning a pump (~40%). In response to a recent DOE mandate for improved pump efficiency pump manufacturers are preparing for the changes that the impending regulations will bring, including design improvements. This mandate also establishes a need for new low cost pump efficiency measurement systems. The standard industry definition of pump efficiency is the mechanical water horsepower delivered divided by the electrical horsepower input to the motor. KCF Technologies has developed a new sensor measurement technique to estimate fluid pump efficiency using a thermodynamic approach. KCF Technologies applied for a SBV grant with ORNL as the research partner. KCF needed a research partner with the proper facilities to demonstrate the efficacy of its wireless sensor unit for measuring pump efficiency. The ORNL Building Technologies Research and Integration Center (BTRIC) test resources were used to test and demonstrate the successful measurement of pump efficiency with the KCF sensor technology. KCF is now working on next steps to commercialize this sensing technology.
Report Numbers:
E 1.99:ornl/tm-2017/8
ornl/tm-2017/8
Subject(s):
Other Subject(s):
Note:
Published through SciTech Connect.
01/23/2017.
"ornl/tm-2017/8"
"BT0309000"
"CEBT288"
"CRADA/NFE-16-06133"
David L. Fugate; Xiaobing Liu; Anthony C. Gehl; Gary Koopmann.
Funding Information:
AC05-00OR22725
View MARC record | catkey: 23767434