Descriptive and Inferential Statistics for Supervising and Monitoring the Operation of PV Plants
Vergura, S.
Acciani, G.
Amoruso, V.
Patrono, G.E.
Vacca, F.
Dipt. di Elettrotec. ed Elettron., Politec. di Bari, Bari, Italy;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: Nov. 2009
Volume: 56,
Issue: 11
On page(s): 4456-4464
ISSN: 0278-0046
INSPEC Accession Number: 10909318
Digital Object Identifier: 10.1109/TIE.2008.927404
First Published: 2008-06-26
Current Version Published: 2009-10-09
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 connected.
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
