The categorisation of electricity users is carried out by Distributor System Operators (DSOs) and retailers to create synthetic load profiles. Initially, some macro-categories are defined based on general attributes of the users, such as voltage level and type of users (residential/non-residential). Then, statistical analyses and clustering techniques are applied to create appropriate groups of users and compute the load profiles for each group. This paper considers the DSO point of view and proposes the definition of additional internal categories, determined by using mono-, two- and three-dimensional features based on reference power, energy, and utilisation. The internal categories contain subsets of users with similar characteristics, which are then sent to the subsequent steps of the procedure for computing the load profiles. The internal categories are formed by executing a clustering algorithm on annual data, or adopting a consensus-based procedure that evaluates the results of clustering algorithms executed for each month of the year. The results are presented considering real data obtained during the years 2019 and 2020 for a large set of low-voltage three-phase users. The effects of the severe restrictions due to the COVID-19 pandemic on some monthly energy data in 2020 are also considered in the analysis.
Creation of the Internal Categories for Low-Voltage Three-Phase Electricity Users / Chicco, Gianfranco; Bonansinga, Daniele; Colella, Pietro; Solida, Lorenzo. - In: IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS. - ISSN 0093-9994. - ELETTRONICO. - 60:4(2024), pp. 1-13. [10.1109/tia.2024.3379302]
Creation of the Internal Categories for Low-Voltage Three-Phase Electricity Users
Chicco, Gianfranco;Colella, Pietro;Solida, Lorenzo
2024
Abstract
The categorisation of electricity users is carried out by Distributor System Operators (DSOs) and retailers to create synthetic load profiles. Initially, some macro-categories are defined based on general attributes of the users, such as voltage level and type of users (residential/non-residential). Then, statistical analyses and clustering techniques are applied to create appropriate groups of users and compute the load profiles for each group. This paper considers the DSO point of view and proposes the definition of additional internal categories, determined by using mono-, two- and three-dimensional features based on reference power, energy, and utilisation. The internal categories contain subsets of users with similar characteristics, which are then sent to the subsequent steps of the procedure for computing the load profiles. The internal categories are formed by executing a clustering algorithm on annual data, or adopting a consensus-based procedure that evaluates the results of clustering algorithms executed for each month of the year. The results are presented considering real data obtained during the years 2019 and 2020 for a large set of low-voltage three-phase users. The effects of the severe restrictions due to the COVID-19 pandemic on some monthly energy data in 2020 are also considered in the analysis.File | Dimensione | Formato | |
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Chicco2024Creation_EarlyAccess.pdf
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https://hdl.handle.net/11583/2987185