Identifying PV Module Mismatch Faults by a Thermography-Based Temperature Distribution Analysis

Hu, Yihua; Cao, Wenping; Ma, Jien; Finney, S.J.; Li, David

doi:10.1109/tdmr.2014.2348195

Cited by 137 publications

(67 citation statements)

References 34 publications

(31 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, the authors consider a reasonable threshold of 5% to avoid high rates of false positives in order to identify not all but almost every significant defect in the PV plant. A similar approach is proposed by [32], [33] where the authors classify the severity of faults in three different degrees, namely minor, medium and heavy faults. In this last case part of a module is typically shorted by a bypass diode as an outcome of, for examples, mismatch, cell cracking, partial shading, and increased internal resistance [8].…”

Section: Experimental Analysis and Resultsmentioning

confidence: 99%

Innovative Automated Control System for PV Fields Inspection and Remote Control

Aghaei

Grimaccia

Gonano

et al. 2015

IEEE Trans. Ind. Electron.

136

View full text Add to dashboard Cite

Abstract-Unmanned Aerial Vehicles (UAVs) are becoming a reliable and useful instrument in monitoring and diagnostic services in the energy field. Operation and maintenance is a crucial factor for PV plant inspection and control activities which currently are quite hard to be performed due to manual and dispersive procedures. The automation of the monitoring techniques will become in future an essential task in this market and Unmanned Aerial System (UAS) technology can play a role in it. This paper proposes a novel, comprehensive and innovative approach in order to automate the inspection and prognostic procedure by means of designing a control system in order to provide accurate information on operating conditions of PV plants. The system is able to perform PV systems' monitoring, diagnosis, defects and failures reconnaissance, data processing and to propose remedial actions. In current experimental research, only IR sensor imaging was examined to evaluate thermographic behavior of the PV modules and to build the related image processing algorithm. However, it is possible to easily extend such a procedure in order to manage a larger amount of data. First results of this work have proven that the proposed procedure is very promising being fast, cost effective and adaptable to large PV plants which can be controlled during their entire lifetime.

show abstract

Section: Experimental Analysis and Resultsmentioning

confidence: 99%

Innovative Automated Control System for PV Fields Inspection and Remote Control

Aghaei

Grimaccia

Gonano

et al. 2015

IEEE Trans. Ind. Electron.

136

View full text Add to dashboard Cite

show abstract

“…Therefore, the position of the MPP voltage of the nth peak U mn is mainly determined by the nth PV module. Equation (13) shows that the MPP voltage of the nth PV module U mpn can be expressed as follows:…”

Section: Mpf For a Pv String Under Module-level Pscsmentioning

confidence: 99%

“…These heuristic methods perform extremely well under normal irradiance conditions. However, PV modules are generally installed in outdoor environments, and they are prone to electrical faults as a result of PSCs and hotspots [13]- [14]. It is common to experience PSCs due to dust, clouds or shadows.…”

Section: Introductionmentioning

confidence: 99%

Combining Model-based and Heuristic Techniques for Fast Tracking the Global Maximum Power Point of a Photovoltaic String

Shi¹,

Xue²,

Ling³

et al. 2017

Journal of Power Electronics

View full text Add to dashboard Cite

Under partial shading conditions (PSCs), multiple maximums may be exhibited on the P-U curve of string inverter photovoltaic (PV) systems. Under such conditions, heuristic methods are invalid for extracting a global maximum power point (GMPP); intelligent algorithms are time-consuming; and model-based methods are complex and costly. To overcome these shortcomings, a novel hybrid MPPT (MPF-IP&O) based on a model-based peak forecasting (MPF) method and an improved perturbation and observation (IP&O) method is proposed. The MPF considers the influence of temperature and does not require solar radiation measurements. In addition, it can forecast all of the peak values of the PV string without complex computation under PSCs, and it can determine the candidate GMPP after a comparison. Hence, the MPF narrows the searching range tremendously and accelerates the convergence to the GMPP. Additionally, the IP&O with a successive approximation strategy searches for the real GMPP in the neighborhood of the candidate one, which can significantly enhance the tracking efficiency. Finally, simulation and experiment results show that the proposed method has a higher tracking speed and accuracy than the perturbation and observation (P&O) and particle swarm optimization (PSO) methods under PSCs.

show abstract

“…Hot spots are relatively frequent in current PV modules and this situation will likely persist as the PV module technology is evolving to thinner wafers, which are prone to developing micro-cracks during the manipulation process such as manufacturing, transportation, and installation [6][7][8].…”

Section: Introductionmentioning

confidence: 99%