Development of Nottingham Arc Model for DC Series Arc Modeling in Photovoltaic Panels

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

doi:10.1109/tie.2021.3128915

Cited by 7 publications

(6 citation statements)

References 32 publications

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“…One of the copper rods with a flat tip is the stationary electrode, and the other with a pointed tip is the moving electrode, as shown in Figure 2. The DC arc can be equivalent to a nonlinear resistance; the arc gap's length and current will affect the arc voltage [37]. Once the series arc ignites, the arc voltage drastically increases to 15 V, as shown in Figure 3.…”

Section: Series Arc V-i Characteristicsmentioning

confidence: 99%

Series Arc Fault Characteristics and Detection Method of a Photovoltaic System

Pang,

Ding

2023

Energies

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The DC arc is the main cause of fire in photovoltaic (PV) systems. This is due to the fact that the DC arc has no zero-crossing point and is prone to stable combustion. Failure to detect it in a timely manner can seriously endanger the PV system. This study analyzes the influences of the series arc and the maximum power point tracking (MPPT) algorithm on the PV output characteristics based on the PV equivalent circuit module. The PV voltage and current variation characteristics are obtained when the series arc occurs. The findings indicate that the input voltage of the converter remains unchanged due to the MPPT algorithm before and after the series arc occurs. Furthermore, the PV faulty string output current will drastically decrease when the series arc fault occurs. On this basis, a series arc detection method based on the current change is proposed, suppressing the combustion of the series arc by increasing the target voltage of the MPPT algorithm. The experimental results show that the proposed method can effectively detect and extinguish the series arc in the PV system within 0.6 s. Compared to the other methods, the proposed method can be integrated into the PV system without additional hardware.

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Section: Series Arc V-i Characteristicsmentioning

confidence: 99%

Series Arc Fault Characteristics and Detection Method of a Photovoltaic System

Pang,

Ding

2023

Energies

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“…6 show the circuit diagrams of DC series and DC shunt motors [26], respectively. For the series DC motor, the armature winding circuit and power equations are given by ( 5), (6), and ( 7) [27] ()…”

Section: A Theoreticallymentioning

confidence: 99%

Efficiency Improvement of Electric Vehicles By Using Winding-Less Rotor Based DC Motor

Ahmed¹,

Mehboob

2022

IJECER

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In electric vehicles (EVs), efficient energy consumption is very important. Based on demand, different electric motor technologies are employed by the manufacturers and are still evolving. This paper analyses the electric motors utilized in electric vehicles such as DC motor, Brushless DC (BLDC) motor, AC induction motor, permanent magnet synchronous motor (PMSM), switched reluctance motor (SRM), and permanent magnet synchronous reluctance motor (PM-SynRM). The advantages and disadvantages correspond to traction motors are pointed out. The main drawback is the power losses in the armature windings of the motors that reduce the overall efficiency and reduce the run per charge of EV due to additional power consumption from the battery pack. To reduce these losses, the authors have proposed a system that is more efficient as the windings from the rotor have been replaced by permanent magnets. Therefore, the power losses in armature windings have been eliminated, and reduced the power consumption by the motor from the battery pack, subsequently, the run per charge of EV has been increased. The overall efficiency of EVs has been increased to almost 100% by the proposed system. This claim is supported theoretically, graphically, as well as practically and presented in the results section of the paper. Finally, the conclusions have been made on the traction motors used in the proposed EVs model.

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“…The widespread adoption of DC distribution systems in renewable energy systems, electric vehicles, microgrids, and electric aircraft brings numerous benefits but also introduces challenges associated with faults in these systems [1,2]. The DC voltage levels above 100 V at busbars, combined with numerous connections, elevate the probability of arc fault occurrences [3]. Additionally, the aging of insulation and the deterioration of terminals during the prolonged operation of DC distribution systems add to the probability of arc faults [4].…”

Section: Introductionmentioning

confidence: 99%

DC Series Arc Fault Diagnosis Scheme Based on Hybrid Time and Frequency Features Using Artificial Learning Models

Dang,

Kwak,

Choi

2024

Machines

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DC series arc faults pose a significant threat to the reliability of DC systems, particularly in DC generation units where aging components and high voltage levels contribute to their occurrence. Recognizing the severity of this issue, this study aimed to enhance DC arc fault detection by proposing an advanced recognition procedure. The methodology involves a sophisticated combination of current filtering using the Three-Sigma Rule in the time domain and the removal of switching noise in the frequency domain. To further enhance the diagnostic capabilities, the proposed method utilizes time and frequency signals generated from power supply-side signals as a reference input. The time–frequency features extracted from the filtered signals are then combined with artificial learning models. This fusion of advanced signal processing and machine learning techniques aims to capitalize on the strengths of both domains, providing a more comprehensive and effective means of detecting arc faults. The results of this detection process validate the effectiveness and consistency of the proposed DC arc failure identification schematic. This research contributes to the advancement of fault detection methodologies in DC systems, particularly by addressing the challenges associated with distinguishing arc-related distortions, ultimately enhancing the safety and dependability of DC electrical systems.

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Development of Nottingham Arc Model for DC Series Arc Modeling in Photovoltaic Panels

Cited by 7 publications

References 32 publications

Series Arc Fault Characteristics and Detection Method of a Photovoltaic System

Series Arc Fault Characteristics and Detection Method of a Photovoltaic System

Efficiency Improvement of Electric Vehicles By Using Winding-Less Rotor Based DC Motor

DC Series Arc Fault Diagnosis Scheme Based on Hybrid Time and Frequency Features Using Artificial Learning Models

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