I n this paper, an evaluation approach for analyzing the weather’s impact on the number of daily outages in the urban distribution system is explored. By dividing the number of outag es into two levels, the task could be carried out as a binary classification problem. In this study, the actual outage data from the distribution system operator is analyzed together with the local weat her condition records. First, the tendency of differen t outage levels to weather conditions is described by the Principal Component Analysis (PCA). Then, the Support Vector Machine (SVM) algorithm is adopted to build the classification model for predicting the outag e levels based on the weather condition. An oversampling method is introduced to manage the severe imbalance between the two outage levels. At the end, the performance of the classification model is assessed with the Receiver Operating Characteristic (ROC) curve.
Discussion about the Weather Impact on the Daily Outages in Urban Distribution System / Zhang, Yang; Mazza, Andrea; Bompard, ETTORE FRANCESCO; Roggero, Emiliano; Galofaro, Giuliana. - ELETTRONICO. - (2019). (Intervento presentato al convegno 54th International Universities Power Engineering Conference (UPEC 2019) tenutosi a Bucharest (Romania) nel 3-6 September 2019) [10.1109/UPEC.2019.8893522].
Discussion about the Weather Impact on the Daily Outages in Urban Distribution System
Yang Zhang;Andrea Mazza;Ettore Bompard;
2019
Abstract
I n this paper, an evaluation approach for analyzing the weather’s impact on the number of daily outages in the urban distribution system is explored. By dividing the number of outag es into two levels, the task could be carried out as a binary classification problem. In this study, the actual outage data from the distribution system operator is analyzed together with the local weat her condition records. First, the tendency of differen t outage levels to weather conditions is described by the Principal Component Analysis (PCA). Then, the Support Vector Machine (SVM) algorithm is adopted to build the classification model for predicting the outag e levels based on the weather condition. An oversampling method is introduced to manage the severe imbalance between the two outage levels. At the end, the performance of the classification model is assessed with the Receiver Operating Characteristic (ROC) curve.File | Dimensione | Formato | |
---|---|---|---|
Zhang19_UPEC_web.pdf
accesso aperto
Tipologia:
1. Preprint / submitted version [pre- review]
Licenza:
PUBBLICO - Tutti i diritti riservati
Dimensione
2.44 MB
Formato
Adobe PDF
|
2.44 MB | Adobe PDF | Visualizza/Apri |
08893522.pdf
non disponibili
Descrizione: Articolo principale versione post-print editoriale
Tipologia:
2a Post-print versione editoriale / Version of Record
Licenza:
Non Pubblico - Accesso privato/ristretto
Dimensione
396.54 kB
Formato
Adobe PDF
|
396.54 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11583/2751855