Methodology to characterize urban areas with similar daily electricity load curves using smart meters and census information (Montevideo-Uruguay)

Pedro Chévez and Dante Barbero

Energy & Environment, 2024, vol. 35, issue 7, 3483-3503

Abstract: Given the massive deployment of smart meters at international level, it is necessary to develop methodologies to extract knowledge from the data that they can provide. To this end, it is necessary to associate energy, socio-demographic and/or technical-constructive data, because this is the only way to identify profiles with their corresponding relevant variables or drivers. The usual problem is that socio-technical information about users is limited or non-existent, as it is costly to collect. Consequently, this work presents as a novelty the use of census information to characterize groups of urban segments with similar daily electricity load curves, which avoids the need to collect socio-technical information through specific surveys or direct measurements. In this way, relevant variables are identified in the determination of consumption patterns in the study case (Montevideo-Uruguay) and they are used to infer the daily behavior of those sectors of the city that don’t have this information.

Keywords: Smart meters; electricity demand management; clustering; load curve; electricity demand (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:engenv:v:35:y:2024:i:7:p:3483-3503

DOI: 10.1177/0958305X231169011

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