The monitoring of photovoltaic (PV) systems is important for the optimization of their efficiency. In this paper, a low-cost smart multisensor architecture equipped with voltage, current, irradiance, temperature, and inertial sensors, for the monitoring (at the panel level) of a PV system, is presented with the aim of detecting the causes of efficiency losses. The system is based on a Wireless Sensor Networks with sensing nodes installed on each PV panel. The acquired data are then transferred to a service center where dedicated paradigms continuously perform the assessment of electrical efficiency as well the estimation of correlated causes, at the single panel level. In this paper, the detection of critical faults (temporary and permanent shadowing, dirtying, and anomalous aging) is addressed. The methodology adopted to estimate efficiency losses and related causes is based on the comparison between the measured efficiency of each PV panel and the nominal one estimated in the real operating conditions. Moreover, the anomalous aging estimation is based on the five parameter model approach that exploits a dedicated minimization paradigm to analyze the mismatch between the nominal current-voltage model of the PV panel and the measured one. The main advantage of the proposed approach is the continuous monitoring of PV plants and the assessment of possible causes of power inefficiency at the PV panel level, allowing for the implementation of a really efficient distributed fault diagnosis system. The experimental results are presented along with the analysis of the uncertainty affecting the measurement system.

Sentinella: Smart Monitoring of Photovoltaic Systems at Panel Level

ANDO', Bruno;BAGLIO, Salvatore;TINA, Giuseppe Marco;Ventura C.
2015-01-01

Abstract

The monitoring of photovoltaic (PV) systems is important for the optimization of their efficiency. In this paper, a low-cost smart multisensor architecture equipped with voltage, current, irradiance, temperature, and inertial sensors, for the monitoring (at the panel level) of a PV system, is presented with the aim of detecting the causes of efficiency losses. The system is based on a Wireless Sensor Networks with sensing nodes installed on each PV panel. The acquired data are then transferred to a service center where dedicated paradigms continuously perform the assessment of electrical efficiency as well the estimation of correlated causes, at the single panel level. In this paper, the detection of critical faults (temporary and permanent shadowing, dirtying, and anomalous aging) is addressed. The methodology adopted to estimate efficiency losses and related causes is based on the comparison between the measured efficiency of each PV panel and the nominal one estimated in the real operating conditions. Moreover, the anomalous aging estimation is based on the five parameter model approach that exploits a dedicated minimization paradigm to analyze the mismatch between the nominal current-voltage model of the PV panel and the measured one. The main advantage of the proposed approach is the continuous monitoring of PV plants and the assessment of possible causes of power inefficiency at the PV panel level, allowing for the implementation of a really efficient distributed fault diagnosis system. The experimental results are presented along with the analysis of the uncertainty affecting the measurement system.
2015
Photovoltaic Panel; Modeling; Monitoring
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/17232
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