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Title: Recovery Act: Advanced Load Identification and Management for Buildings

Abstract

In response to the U.S. Department of Energy (DoE)’s goal of achieving market ready, net-zero energy residential and commercial buildings by 2020 and 2025, Eaton partnered with the Department of Energy’s National Renewable Energy Laboratory (NREL) and Georgia Institute of Technology to develop an intelligent load identification and management technology enabled by a novel “smart power strip” to provide critical intelligence and information to improve the capability and functionality of building load analysis and building power management systems. Buildings account for 41% of the energy consumption in the United States, significantly more than either transportation or industrial. Within the building sector, plug loads account for a significant portion of energy consumption. Plug load consumes 15-20% of building energy on average. As building managers implement aggressive energy conservation measures, the proportion of plug load energy can increase to as much as 50% of building energy leaving plug loads as the largest remaining single source of energy consumption. This project focused on addressing plug-in load control and management to further improve building energy efficiency accomplished through effective load identification. The execution of the project falls into the following three major aspects; An intelligent load modeling, identification and prediction technology was developed tomore » automatically determine the type, energy consumption, power quality, operation status and performance status of plug-in loads, using electric waveforms at a power outlet level. This project demonstrated the effectiveness of the developed technology through a large set of plug-in loads measurements and testing; A novel “Smart Power Strip (SPS) / Receptacle” prototype was developed to act as a vehicle to demonstrate the feasibility of load identification technology as a low-cost, embedded solution; and Market environment for plug-in load control and management solutions, in particular, advanced power strips (APSs) was studied. The project evaluated the market potential for Smart Power Strips (SPSs) with load identification and the likely impact of a load identification feature on APS adoption and effectiveness. The project also identified other success factors required for widespread APS adoption and market acceptance. Even though the developed technology is applicable for both residential and commercial buildings, this project is focused on effective plug-in load control and management for commercial buildings, accomplished through effective load identification. The project has completed Smart Receptacle (SR) prototype development with integration of Load ID, Control/Management, WiFi communication, and Web Service. Twenty SR units were built, tested, and demonstrated in the Eaton lab; eight SR units were tested in the National Renewable Energy Lab (NREL) for one-month of field testing. Load ID algorithm testing for extended load sets was conducted within the Eaton facility and at local university campuses. This report is to summarize the major achievements, activities, and outcomes under the execution of the project.« less

Authors:
 [1];  [1];  [1];  [1]
  1. Eaton Corporation, Menomonee Falls, WI (United States)
Publication Date:
Research Org.:
Eaton Corporation, Menomonee Falls, WI (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1172882
Report Number(s):
DOE-Eaton-EE0003911
DOE Contract Number:  
EE0003911
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; Load Identification; Nonintrusive Load Monitoring; Power Strip; Receptacle; Outlet; Plug Load; Miscellaneous Electric Loads; Plug Load Management; Building Efficiency

Citation Formats

Yang, Yi, Casey, Patrick, Du, Liang, and He, Dawei. Recovery Act: Advanced Load Identification and Management for Buildings. United States: N. p., 2014. Web. doi:10.2172/1172882.
Yang, Yi, Casey, Patrick, Du, Liang, & He, Dawei. Recovery Act: Advanced Load Identification and Management for Buildings. United States. https://doi.org/10.2172/1172882
Yang, Yi, Casey, Patrick, Du, Liang, and He, Dawei. 2014. "Recovery Act: Advanced Load Identification and Management for Buildings". United States. https://doi.org/10.2172/1172882. https://www.osti.gov/servlets/purl/1172882.
@article{osti_1172882,
title = {Recovery Act: Advanced Load Identification and Management for Buildings},
author = {Yang, Yi and Casey, Patrick and Du, Liang and He, Dawei},
abstractNote = {In response to the U.S. Department of Energy (DoE)’s goal of achieving market ready, net-zero energy residential and commercial buildings by 2020 and 2025, Eaton partnered with the Department of Energy’s National Renewable Energy Laboratory (NREL) and Georgia Institute of Technology to develop an intelligent load identification and management technology enabled by a novel “smart power strip” to provide critical intelligence and information to improve the capability and functionality of building load analysis and building power management systems. Buildings account for 41% of the energy consumption in the United States, significantly more than either transportation or industrial. Within the building sector, plug loads account for a significant portion of energy consumption. Plug load consumes 15-20% of building energy on average. As building managers implement aggressive energy conservation measures, the proportion of plug load energy can increase to as much as 50% of building energy leaving plug loads as the largest remaining single source of energy consumption. This project focused on addressing plug-in load control and management to further improve building energy efficiency accomplished through effective load identification. The execution of the project falls into the following three major aspects; An intelligent load modeling, identification and prediction technology was developed to automatically determine the type, energy consumption, power quality, operation status and performance status of plug-in loads, using electric waveforms at a power outlet level. This project demonstrated the effectiveness of the developed technology through a large set of plug-in loads measurements and testing; A novel “Smart Power Strip (SPS) / Receptacle” prototype was developed to act as a vehicle to demonstrate the feasibility of load identification technology as a low-cost, embedded solution; and Market environment for plug-in load control and management solutions, in particular, advanced power strips (APSs) was studied. The project evaluated the market potential for Smart Power Strips (SPSs) with load identification and the likely impact of a load identification feature on APS adoption and effectiveness. The project also identified other success factors required for widespread APS adoption and market acceptance. Even though the developed technology is applicable for both residential and commercial buildings, this project is focused on effective plug-in load control and management for commercial buildings, accomplished through effective load identification. The project has completed Smart Receptacle (SR) prototype development with integration of Load ID, Control/Management, WiFi communication, and Web Service. Twenty SR units were built, tested, and demonstrated in the Eaton lab; eight SR units were tested in the National Renewable Energy Lab (NREL) for one-month of field testing. Load ID algorithm testing for extended load sets was conducted within the Eaton facility and at local university campuses. This report is to summarize the major achievements, activities, and outcomes under the execution of the project.},
doi = {10.2172/1172882},
url = {https://www.osti.gov/biblio/1172882}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Feb 12 00:00:00 EST 2014},
month = {Wed Feb 12 00:00:00 EST 2014}
}