This paper proposes a procedure, based on both descriptive and inferential statistics for diagnosis of PV plants. This study aims to developing an algorithm able to recognize accurately among a degradation status and a system abnormality before a fault occurs. The statistical approach, based on the ANOVA and Kruskal-Wallis tests, is effective in locating abnormal operating conditions even in the presence of a reduced availability of energy measures. The proposed algorithm has been applied to a case study and advantages and limitations are presented
Inferential Statistics for Monitoring and Fault Forecasting of PV Plants / Vergura, Silvano; Acciani, Giuseppe; Amoruso, V; Patrono, G.. - (2008), pp. 2414-2419. (Intervento presentato al convegno IEEE International Symposium on Industrial Electronics, ISIE 2008 tenutosi a Cambridge, UK nel 30th June - 2nd July 2008) [10.1109/ISIE.2008.4677264].
Inferential Statistics for Monitoring and Fault Forecasting of PV Plants
VERGURA, Silvano;ACCIANI, Giuseppe;
2008-01-01
Abstract
This paper proposes a procedure, based on both descriptive and inferential statistics for diagnosis of PV plants. This study aims to developing an algorithm able to recognize accurately among a degradation status and a system abnormality before a fault occurs. The statistical approach, based on the ANOVA and Kruskal-Wallis tests, is effective in locating abnormal operating conditions even in the presence of a reduced availability of energy measures. The proposed algorithm has been applied to a case study and advantages and limitations are presentedI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
