Experimental and data collection methods for a large-scale smart grid deployment: Methods and first results
| Autor: | Joshua D. Rhodes, Wesley Cole, Chioke B. Harris, Chris L. Holcomb, Michael E. Webber, Alexis Kwasinski, Robert L. Fares, Roger D. Duncan, Thomas F. Edgar, Harsha Kumar, David Walling, Paul A. Navrátil, Ariane L. Beck, Kazunori Nagasawa, Colin M. Meehan, Charles R. Upshaw |
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| Rok vydání: | 2014 |
| Předmět: |
Engineering
Data collection Database Data stream mining business.industry Mechanical Engineering Photovoltaic system Ranging Building and Construction computer.software_genre Supercomputer Pollution Industrial and Manufacturing Engineering General Energy Smart grid Software deployment Electrical and Electronic Engineering business computer Energy (signal processing) Simulation Civil and Structural Engineering |
| Zdroj: | Energy. 65:462-471 |
| ISSN: | 0360-5442 |
| Popis: | This paper has two objectives: 1) to describe the experimental and data collection methods for a large-scale smart grid deployment in Austin, Texas, and 2) to provide results based on those data. As of October 2012, the test bed was comprised of 1) 250 homes concentrated in a single neighborhood all built after 2007, and 2) 160 homes distributed throughout Austin with ages ranging from 10 to 92 years old. This experiment includes 200 electric monitoring systems (15-s resolution), 211 electric monitoring systems (1-min), 182 gas meters (2-cubic foot), and 51 water meters (1 gallon) and many of the monitored homes also have energy audits and homeowner surveys. The test bed also includes 185 rooftop PV (photovoltaic) installations and 50 electric vehicles in the same neighborhood. Data streams were automated and gathered at a supercomputing facility at UT-Austin yielding 250 GB (2.95 × 10 9 records) of data in the first year. This paper describes the baseline study and monitoring methods, characterizes the study participants, and provides some first results about residential energy use. These results include a negative correlation between energy use and knowledge about energy as well as a possible positive correlation between energy use and some rebates. |
| Databáze: | OpenAIRE |
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