An efficient algorithm for extracting appliance-time association using smart meter data
Demand Response (DR) programs play a significant role for developing energy management solutions. Gaining home residents trust and respecting their appliances usage preferences are essential factors for promoting these programs. Extracting resident's usage behaviour is a challenging task with t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019-08-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844019358864 |
| Summary: | Demand Response (DR) programs play a significant role for developing energy management solutions. Gaining home residents trust and respecting their appliances usage preferences are essential factors for promoting these programs. Extracting resident's usage behaviour is a challenging task with the infinite massive amount of data being generated from smart meters. The main contribution of this paper is to extract temporal association patterns of energy consumption at appliance level. The proposed approach extends the Utility-oriented Temporal Association Rules Mining (UTARM) algorithm to discover appliances usage preference at a time. The results achieved from the proposed work succeeded to discover appliance-time association considering appliances usage priority as a utility factor with respect to the 24-hours of the day as a temporal partitioning factor. |
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| ISSN: | 2405-8440 |