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학술지 Projecting Household-scale Utility Usage: A Case Study Using a Long-term Dataset
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저자
박종준, 김현학, 허태욱, 유승목, 고정길
발행일
201605
출처
International Journal of Sensor Networks, v.20 no.4, pp.264-277
ISSN
1748-1279
출판사
Inderscience
DOI
https://dx.doi.org/10.1504/IJSNET.2016.076703
협약과제
12MC5400, 공동거주지 에너지비용절감(최고20%)을 위한 협력형 센싱정보를 이용한 프로액티브 에너지 관리기술개발, 유승목
초록
The deployment of advanced metring infrastructures allows suppliers and consumers to better understand the utility supply and usage chain. Data from these systems are typically used to analyse utility usage in a large scale, but when observed at smaller scales, we can enable a number of interesting new application. In this work we use utility usage data collected from 300 households over three years and perform detailed analysis to understand per-household utility usage patterns.We showthat per-household utility usage data introduces high variances and lowcorrelations among different households even if they are co-located in similar geographical regions. Using our findings, we introduce AUUP, an adaptive utility usage prediction scheme that combines the output from different (existing) forecasting schemes to adaptively make smart small-scale utility usage predictions. Our evaluations show that AUUP effectively reduces the prediction errors of artificial neural networks, LMS and Kalman filter-based AR model prediction schemes.
키워드
Adaptive utility usage prediction, Household-scale utility management
KSP 제안 키워드
AR Model, Artificial neural networks, Case studies, Co-located, Data collected, Filter-based, Geographical regions, Prediction error, Prediction scheme, Small-scale, Utility Management