A Malfunction Detection Method for Individual Photovoltaic Modules

Masaya Iwata, Yuji Kasai, Eiichi Takahashi, Masahiro Murakawa

2013

Abstract

Although photovoltaic (PV) modules occasionally fail, it is difficult to identify which module is malfunctioning. In order to detect malfunctioning PV modules, we have developed a malfunction detection method for individual PV modules by continuously monitoring their data. This method can automatically identify a malfunctioning module where output power declines at an early stage. Thus, the method provides faster and more accurate detection of malfunctions. Moreover, the method considerably reduces workloads for maintenance personnel because it eliminates the need for conventional inspection procedures to identify a malfunctioning module. A feature of the method is the utilization of two kinds of information among the PV modules, namely, spatial and temporal correlations, to distinguish between generation declines due to some malfunction and those due to climate conditions. To confirm the effectiveness of the method, we conducted a malfunction-detection experiment with actual data from our PV module monitoring system which we have already implemented. The experiment used 24 PV modules installed within the monitoring system, and simulated a malfunction by covering 10% of a module. The system was able to detect the period of the simulated malfunction, which confirms the effectiveness of the method.

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Paper Citation


in Harvard Style

Iwata M., Kasai Y., Takahashi E. and Murakawa M. (2013). A Malfunction Detection Method for Individual Photovoltaic Modules . In Proceedings of the 2nd International Conference on Smart Grids and Green IT Systems - Volume 1: SMARTGREENS, ISBN 978-989-8565-55-6, pages 179-184. DOI: 10.5220/0004378601790184


in Bibtex Style

@conference{smartgreens13,
author={Masaya Iwata and Yuji Kasai and Eiichi Takahashi and Masahiro Murakawa},
title={A Malfunction Detection Method for Individual Photovoltaic Modules},
booktitle={Proceedings of the 2nd International Conference on Smart Grids and Green IT Systems - Volume 1: SMARTGREENS,},
year={2013},
pages={179-184},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004378601790184},
isbn={978-989-8565-55-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Smart Grids and Green IT Systems - Volume 1: SMARTGREENS,
TI - A Malfunction Detection Method for Individual Photovoltaic Modules
SN - 978-989-8565-55-6
AU - Iwata M.
AU - Kasai Y.
AU - Takahashi E.
AU - Murakawa M.
PY - 2013
SP - 179
EP - 184
DO - 10.5220/0004378601790184