An Enhanced Cassie–Mayr-Based Approach for DC Series Arc Modeling in PV Systems

Jalil, Masoud; Samet, Haidar; Ghanbari, Teymoor; Tajdinian, Mohsen

doi:10.1109/tim.2021.3124832

Cited by 27 publications

(14 citation statements)

References 33 publications

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“…It is possible to categorize these methods into two categories: electrical and nonelectrical methods. Electrical methods are usually considered and potentially mitigated using statistical [9,10] or signal processing methods [11]. For example, in [9], authors have proposed an enhanced Cassie-Mayr-Based approach for detecting DC series arcing in PV systems.…”

Section: Introductionmentioning

confidence: 99%

“…Electrical methods are usually considered and potentially mitigated using statistical [9,10] or signal processing methods [11]. For example, in [9], authors have proposed an enhanced Cassie-Mayr-Based approach for detecting DC series arcing in PV systems. However, the same problem was investigated by [10] by adopting a neural network and receiving signal strength indicators.…”

Section: Introductionmentioning

confidence: 99%

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Photovoltaic Bypass Diode Fault Detection Using Artificial Neural Networks

Dhimish

Tyrrell

2023

IEEE Trans. Instrum. Meas.

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Due to the importance of determining faulty bypass diodes in photovoltaic systems, faulty bypass diodes have been of widespread interest in recent years due to their importance to improving PV system durability, operation, and overall safety. This paper presents new work in developing an artificial intelligence (AI) based model using the principles of artificial neural networks (ANN) to detect short and open PV bypass diodes fault conditions. With only three inputs from the PV system, namely the output power, short-circuit current, and open-circuit voltage, the developed ANN model can determine whether the PV bypass diodes are defective. In the experimentally validated case of short and open bypass diodes, 93.6% and 93.3% of faulty bypass diodes can be detected. Furthermore, the developed ANN model has an average precision and sensitivity of 96.4% and 92.6%, respectively.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Photovoltaic Bypass Diode Fault Detection Using Artificial Neural Networks

Dhimish

Tyrrell

2023

IEEE Trans. Instrum. Meas.

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“…Series arcs typically occur when a conductor connected in series with the load is broken, or due to a loose connection or a defect in the insulation of a wire. Series arc currents are often discontinuous and they are below the trip currents magnitude of conventional thermal/magnetic circuit breakers, so they often produce long-duration overheating of wiring systems, often leading to electric shock hazards [23]. As a result, they pyrolyze the surrounding insulation materials, generating char, a solid carbon-rich compound.…”

Section: Introductionmentioning

confidence: 99%

Arc Fault Protections for Aeronautic Applications: A Review Identifying the Effects, Detection Methods, Current Progress, Limitations, Future Challenges, and Research Needs

Riba¹,

Moreno-Eguilaz²,

Ortega³

2022

IEEE Trans. Instrum. Meas.

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Arc faults are serious discharges, damaging insulation systems and triggering electrical fires. This is a transversal topic, affecting from residential to aeronautic applications. Current commercial aircrafts are being progressively equipped with arc fault protections. With the development of more electric aircrafts (MEA), future airliners will require more electrical power to enhance fuel economy, save weight and reduce emissions. The ultimate goal of MEAs is electrical propulsion, where fault management devices will have a leading role, because aircraft safety is of utmost importance. Therefore, current fault management devices must evolve to fulfill the safety requirements of electrical propelled aircrafts. To deal with the increased electrical power generation, the distribution voltage must be raised, thus leading to new electrical fault types, in particular arc tracking and series arcing, which are further promoted by the harsh environments typical of aircraft systems, i.e., low pressure, extreme humidity and a wide range of temperatures. Therefore, the development of specific electrical protections which are able to protect against these fault types is a must. This paper reviews the state-of-theart of electrical protections for aeronautic applications, identifying the current status and progress, their drawbacks and limitations, the future challenges and research needs to fulfill the future requirements of MEAs, with a special emphasis on series arc faults due to arc tracking, because of difficulty in detecting such low-energy faults in the early stage and the importance and harmful effects of tracking activity in cabling insulation systems. This technological and scientific review is based on a deep analysis of research and conference papers, official reports, white papers and international regulations.

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“…Arc tracking activity releases energy and generates different measurable effects [13], including radio waves, sound, visible and ultraviolet light, heat or chemicals such as ozone, NOx and nitric acid, among others [14]. Arc tracking activity tends to pyrolyze the insulation materials surrounding the core of the wire, thus producing a partially conductive path that promotes discontinuous arcing activity of low magnitude that overheats the insulation [15], thus producing more damage. Therefore, the low energy level associated with arc tracking activity in the very early stage makes its detection difficult [16].…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Solar-Blind Gas-Filled Sensors to Detect Electrical Discharges for Low-Pressure Aircraft Applications

Ruiz

Moreno-Eguilaz

Boizieau

et al. 2022

Sensors

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Unpressurized aircraft circuits facilitate the initiation of electrical discharges in wiring systems, with consequent damage to related insulation materials and safety hazards, that can and have already caused severe incidents and accidents. Specific sensors and solutions must be developed to detect these types of faults at a very incipient stage, before further damage occurs. Electrical discharges in air generate the corona effect, which is characterized by emissions of bluish light, which are found in the ultraviolet (UV) and visible spectra. However, due to sunlight interference, the corona effect is very difficult to detect at the very initial stage, so the use of solar-blind sensors can be a possible solution. This work analyzes the feasibility of using inexpensive non-invasive solar-blind sensors in a range of pressures compatible with aircraft environments to detect the electrical discharges at a very incipient stage. Their behavior and sensitivity compared with other alternatives, i.e., an antenna sensor and a CMOS imaging sensor, is also assessed. Experimental results presented in this paper show that the analyzed solar-blind sensors can be applied for the on-line detection of electrical discharges in unpressurized aircraft environments at the very initial stage, thus facilitating and enabling the application of predictive maintenance strategies. They also offer the possibility to be combined with existing electrical protections to expand their capabilities and improve their sensitivity to detect very early discharges, thus allowing the timely identification of their occurrence.

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An Enhanced Cassie–Mayr-Based Approach for DC Series Arc Modeling in PV Systems

Cited by 27 publications

References 33 publications

Photovoltaic Bypass Diode Fault Detection Using Artificial Neural Networks

Photovoltaic Bypass Diode Fault Detection Using Artificial Neural Networks

Arc Fault Protections for Aeronautic Applications: A Review Identifying the Effects, Detection Methods, Current Progress, Limitations, Future Challenges, and Research Needs

Performance Evaluation of Solar-Blind Gas-Filled Sensors to Detect Electrical Discharges for Low-Pressure Aircraft Applications

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