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Using Public Participation to Improve MELs Energy Data Collection
Author(s) -
Iris Cheung,
Margarita Kloss,
Rich Brown,
Alan Meier
Publication year - 2014
Language(s) - English
Resource type - Reports
DOI - 10.2172/1129521
Subject(s) - data collection , protocol (science) , crowdsourcing , electricity meter , computer science , reliability (semiconductor) , citizen science , metering mode , energy consumption , reliability engineering , data science , power (physics) , engineering , world wide web , electrical engineering , statistics , mathematics , medicine , mechanical engineering , physics , alternative medicine , botany , pathology , quantum mechanics , biology
Miscellaneous Electric Loads (MELs) have proliferated in the last decade, and comprise an increasing share of building energy consumption. Because of the diversity of MELs and our lack of understanding about how people use them, large-scale data collection is needed to inform meaningful energy reduction strategies. Traditional methods of data collection, however, usually incur high labor and metering equipment expenses. As an alternative, this paper investigates the feasibility of crowdsourcing data collection to satisfy at least part of the data collection needs with acceptable accuracy. This study assessed the reliability and accuracy of crowdsourced data, by recruiting over 20 volunteers (from the 2012 Lawrence Berkeley Lab, Open House event) to test our crowdsourcing protocol. The protocol asked volunteers to perform the following tasks for three test products with increasing complexity - record power meter and product characteristics, identify all power settings available, and report the measured power. Based on our collected data and analysis, we concluded that volunteers performed reasonably well for devices with functionalities with which they are familiar, and might not produce highly accurate field measurements for complex devices. Accuracy will likely improve when participants are measuring the power used by devices in their home which they know how to operate, by providing more specific instructions including instructional videos. When integrated with existing programs such as the Home Energy Saver tool, crowdsourcing data collection from individual homeowners has the potential to generate a substantial amount of information about MELs energy use in homes.

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