The determination of secondary substations load profiles may facilitate distribution system operators to better forecast, plan and operate their distribution networks. The changing in load and coincidence factors due to the high penetration of distributed generators and loads such as electric vehicles, heating ventilation and air conditioning systems, induction stoves, highlights that standard load profiles are not adapted to the current evolution of the power system. As a result, load profiles analysis has become more significant and valuable. This paper deals with the analysis and clustering of aggregate load profiles by means of principal component analysis. Starting from an extensive field measurement-based database of secondary substations daily load profiles, we used principal component analysis to extract the main components and to reduce data dimension. Thanks to the most significant principal components secondary substations are groups in homogeneous clusters labelled with a standard load profile. The proposed methodology was applied to real load profiles gathered from UNARETI, the distribution system operator of Milano.

A Method to Analyzing and Clustering Aggregate Customer Load Profiles Based on PCA / Bosisio, Alessandro; Berizzi, Alberto; Vicario, Andrea; Morotti, Andrea; Greco, Bartolomeo; Iannarelli, Gaetano; Le, Dinh-Duong. - (2020). (Intervento presentato al convegno 2020 5th International Conference on Green Technology and Sustainable Development (GTSD) tenutosi a Ho Chi Minh City, Vietnam).

A Method to Analyzing and Clustering Aggregate Customer Load Profiles Based on PCA

Bartolomeo Greco;Gaetano Iannarelli;
2020

Abstract

The determination of secondary substations load profiles may facilitate distribution system operators to better forecast, plan and operate their distribution networks. The changing in load and coincidence factors due to the high penetration of distributed generators and loads such as electric vehicles, heating ventilation and air conditioning systems, induction stoves, highlights that standard load profiles are not adapted to the current evolution of the power system. As a result, load profiles analysis has become more significant and valuable. This paper deals with the analysis and clustering of aggregate load profiles by means of principal component analysis. Starting from an extensive field measurement-based database of secondary substations daily load profiles, we used principal component analysis to extract the main components and to reduce data dimension. Thanks to the most significant principal components secondary substations are groups in homogeneous clusters labelled with a standard load profile. The proposed methodology was applied to real load profiles gathered from UNARETI, the distribution system operator of Milano.
2020
2020 5th International Conference on Green Technology and Sustainable Development (GTSD)
Principal component analysis , Loading , Data mining , Sustainable development , Standards , Substations , Correlation
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
A Method to Analyzing and Clustering Aggregate Customer Load Profiles Based on PCA / Bosisio, Alessandro; Berizzi, Alberto; Vicario, Andrea; Morotti, Andrea; Greco, Bartolomeo; Iannarelli, Gaetano; Le, Dinh-Duong. - (2020). (Intervento presentato al convegno 2020 5th International Conference on Green Technology and Sustainable Development (GTSD) tenutosi a Ho Chi Minh City, Vietnam).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1615517
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