Statistical fault detection in photovoltaic systems

Abstract

Faults in photovoltaic (PV) systems, which can result in energy loss, system shutdown or even serious safety breaches, are often difficult to avoid. Fault detection in such systems is imperative to improve their reliability, productivity, safety and efficiency. Here, an innovative model-based fault-detection approach for early detection of shading of PV modules and faults on the direct current (DC) side of PV systems is proposed. This approach combines the flexibility, and simplicity of a one-diode model with the extended capacity of an exponentially weighted moving average (EWMA) control chart to detect incipient changes in a PV system. The one-diode model, which is easily calibrated due to its limited calibration parameters, is used to predict the healthy PV array’s maximum power coordinates of current, voltage and power using measured temperatures and irradiances. Residuals, which capture the difference between the measurements and the predictions of the one-diode model, are generated and used as fault indicators. Then, the EWMA monitoring chart is applied on the uncorrelated residuals obtained from the one-diode model to detect and identify the type of fault. Actual data from the grid-connected PV system installed at the Renewable Energy Development Center, Algeria, are used to assess the performance of the proposed approach. Results show that the proposed approach successfully monitors the DC side of PV systems and detects temporary shading.Peer ReviewedPostprint (author's final draft

Graphical Diagnosis of Performances in Photovoltaic Systems: A Case Study in Southern Spain

“…The deviation in the production of one of them with respect to the others is a sign of the presence of some type of disturbance that is On the other hand, the presence of faults, for example, in inverter 413, is clearly shown in Figure 8a with differences in the output, which may be even greater than 80% of the nominal power of the array. There are numerous authors who model the production of the PV plant and compare the actual production with that obtained by the model in order to verify the presence of faults in the installation [25][26][27][28][29][30][31]. Another option is, as presented in this work, to compare the production of arrays that are located together and exposed to the same conditions.…”

“…The diagnosis of the operating mode and fault detection in PV plants is increasingly attracting the interest of researchers [25][26][27][28][29][30][31], and numerous papers have been published in the last few years dedicated to analyzing the operation and performance of the components of working PV plants [4,. Compared to most previous publications, where usually only the daily and/or monthly values of yield and loss indexes are represented, layering the data on a color map allows simultaneously displaying all instantaneous data registered throughout the monitoring period, even if it comprises several years, easing the comprehension and interpretation of large amounts of data.…”

Online model-based fault detection for grid connected PV systems monitoring

“…INTRODUCTION Photovoltaic (PV) systems are continuously exposed to many potential external interferences or faults that can cause significant loss of the power production. Faults in DC side of PV systems are often difficult to avoid and can result in energy loss, system shutdown or even in serious safety concerns [1]. For example, two PV facilities in the US (a 383 KWp PV array in Bakersfield, CA and a 1.208 MWp power plant in Mount Holly, NC) burned in 2009 and 2011, respectively [2].…”

“…In single diode model (SDM) based methods, the unknown electrical parameters of the employed PV module are firstly identified using an efficient strategy [1,6], following with maximum power point (MPP) prediction approach based on real onsite climate data measurements.…”

“…In fact the efficiency of model-based methods depends deeply on the accuracy of the used model which could not been always guaranteed under practical operation. In other side, the main issue of historybased method is that they require the availability of a relevant database that describes the system performances under healthy and faulty operation cases [1].…”