Household Energy Consumption Segmentation Using Hourly Data
The increasing US deployment of residential advanced metering infrastructure (AMI) has made hourly energy consumption data widely available. Using CA smart meter data, we investigate a household electricity segmentation methodology that uses an encoding system with a pre-processed load shape diction...
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| Veröffentlicht in: | IEEE transactions on smart grid 2014-01, Vol.5 (1), p.420-430 |
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| container_title | IEEE transactions on smart grid |
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| creator | Jungsuk Kwac Flora, June Rajagopal, Ram |
| description | The increasing US deployment of residential advanced metering infrastructure (AMI) has made hourly energy consumption data widely available. Using CA smart meter data, we investigate a household electricity segmentation methodology that uses an encoding system with a pre-processed load shape dictionary. Structured approaches using features derived from the encoded data drive five sample program and policy relevant energy lifestyle segmentation strategies. We also ensure that the methodologies developed scale to large data sets. |
| doi_str_mv | 10.1109/TSG.2013.2278477 |
| format | Article |
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| subjects | Clustering Clustering algorithms demand response Dictionaries Electricity Encoding segmentation Shape smart meter data Sociology Statistics variability |
| title | Household Energy Consumption Segmentation Using Hourly Data |
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