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IRMAC: Interpretable Refined Motifs in Binary Classification for Smart Grid Applications. (arXiv:2109.13732v3 [cs.LG] UPDATED)
Nov. 15, 2022, 2:12 a.m. | Rui Yuan, S. Ali Pourmousavi, Wen L. Soong, Giang Nguyen, Jon A. R. Liisberg
cs.LG updates on arXiv.org arxiv.org
Modern power systems are experiencing the challenge of high uncertainty with
the increasing penetration of renewable energy resources and the
electrification of heating systems. In this paradigm shift, understanding
electricity users' demand is of utmost value to retailers, aggregators, and
policymakers. However, behind-the-meter (BTM) equipment and appliances at the
household level are unknown to the other stakeholders mainly due to privacy
concerns and tight regulations. In this paper, we seek to identify residential
consumers based on their BTM equipment, mainly …
More from arxiv.org / cs.LG updates on arXiv.org
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