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Analysis of institutional authors

Gonzalez ACorresponding AuthorGonzalez Bermudez, AnaAuthorBernardos AmAuthorCasar JrAuthor

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November 13, 2023
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Leveraging Smart Meter Data for Adaptive Consumer Profiling

Publicated to:Lecture Notes In Networks And Systems. 749 LNNS 174-184 - 2023-01-01 749 LNNS(), DOI: 10.1007/978-3-031-42529-5_17

Authors: González A; Bernardos AM; Gallego CJ; Casar JR

Affiliations

Information Processing and Telecommunications Center, Universidad Politécnica de Madrid, ETSI Telecomunicación, Madrid, 28040, Spain - Author

Abstract

The growing availability of smart meter data from households is contributing to the digitalization of the energy sector and driving its transformation into new business concepts, such as flexibility markets. This data allows for more precise consumer profiling than ever before, which can be beneficial for demand response modeling, dynamic tariff models… While profiling customers based on time-series consumption data has been extensively studied in the literature, this article offers a different approach by examining the feasibility of profiling new customers using their early data, with varying amounts of smart meter data available (from one month to one year) and considering different approaches of frequency of data (daily, weekly, bi-weekly or monthly). By using an existing dataset (Low Carbon London project, spearheaded by UK Power Networks) for modeling validation and test purposes, the data pipeline in our study employs Dynamic Time Warping K-Means clustering. We compare the similarity of clusters obtained with different data lengths against ground-truth clusters built on all the data by using Rand Index. Results indicate that, on average, one month of data is enough for accurate profiling for a small number of consumer types, although for a larger number it is recommended to use a slot of 6 months. The approach enables effective profiling even on limited data for new customers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

ClusteringClusteringsConsumer profilingDemand responseDtwEnergy sectorK-meansK-means clusteringMetadataProfilingRand indexResponse modelSalesSmart meter dataSmart metersStatistical tests

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Lecture Notes In Networks And Systems, Q4 Agency Scopus (SJR), its regional focus and specialization in Computer Networks and Communications, give it significant recognition in a specific niche of scientific knowledge at an international level.

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-14:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 5 (PlumX).

Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (GONZALEZ BERMUDEZ, ANA) and Last Author (CASAR CORREDERA, JOSE RAMON).

the author responsible for correspondence tasks has been Rodríguez Gonzalez, Ana Belén.