This paper deals with the problem of supervising and monitoring a photovoltaic (PV) plant. First, an offline descriptive and inferential statistical procedure for evaluating the goodness of system performance is presented. Then, an online inferential algorithm for real-time monitoring and fault detection is introduced. The two methodologies utilize the energy output of inverters as input data and are valid for both Gaussian and non-normal distribution of data. The procedures have been tested on a real PV installation, and results are reported for the case of a grid-connected PV plant in Italy for which one PV module over 132 resulted in being badly connected
Descriptive and Inferential Statistics for Supervising and Monitoring the Operation of PV Plants / Vergura, S.; Acciani, G; Amoruso, V.; Patrono, G.; Vacca, F.. - In: IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS. - ISSN 0278-0046. - 56:11(2009), pp. 4456-4464. [10.1109/TIE.2008.927404]
Descriptive and Inferential Statistics for Supervising and Monitoring the Operation of PV Plants
S. VERGURA
;ACCIANI G;
2009-01-01
Abstract
This paper deals with the problem of supervising and monitoring a photovoltaic (PV) plant. First, an offline descriptive and inferential statistical procedure for evaluating the goodness of system performance is presented. Then, an online inferential algorithm for real-time monitoring and fault detection is introduced. The two methodologies utilize the energy output of inverters as input data and are valid for both Gaussian and non-normal distribution of data. The procedures have been tested on a real PV installation, and results are reported for the case of a grid-connected PV plant in Italy for which one PV module over 132 resulted in being badly connectedI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
