The Analysis of Low-Voltage DC Arc behavior on Three Interrupting Phases Based on AC Black-box Arc model

Pyro-breaker, a fast-responding, highly reliable and explosive-driven circuit breaker, is utilized in several Quench Protection Systems (QPS). The commutation process and its parameters are the main technical considerations in the process of designing a new pyro-breaker. The commutation parameters, such as the commutation time and the current change rate, are not only determined by the electrical parameters of the commutation circuit but also the arc behavior during the operation. The arc behavior is greatly affected by the structure and the driving mechanism of the Commutation Section (CS) in the pyro-breaker. The arc model was developed decades ago and the black-box arc model is considered a valid method to study arc behavior. In this paper, the Schavemaker black-box arc model, an improved Mayr-type arc model, is applied to study the commutation process of a newly designed pyro-breaker. Unlike normal circuit breakers, the arc discussed in this paper is discharged in deionized water. A parameter selection method is proposed. The practicability of the method is verified by numerical calculation in Power Systems Computer Aided Design (PSCAD) and experimentally.

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3D Analysis of Low-Voltage Gas-Filled DC Switch Using Simplified Arc Model

Plasma Physics and Technology Journal ◽

10.14311/ppt.2019.1.65 ◽

2019 ◽

Vol 6 (1) ◽

pp. 65-68 ◽

Cited By ~ 1

Author(s):

S. Gortschakow ◽

D. Gonzalez ◽

S. Yu ◽

F. Werner

Keyword(s):

High Speed ◽

Low Voltage ◽

Black Box ◽

Optical Observations ◽

3D Analysis ◽

High Speed Camera ◽

Plasma Model ◽

Arc Model ◽

Arc Current ◽

Electro Magnetic

Electro-magnetic simulations have been used for the visualization of distribution of Lorentz force acting on a DC switching arc in low-voltage contactor. A simplified plasma model (black-box model) was applied for the description of arc conductivity. Arc geometry was gained from the high-speed camera images. Influence of arc position, arc current and of external magnetic field has been studied. Results have been compared with optical observations of the arc dynamics.

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Simulation analysis of DC arc in circuit breaker applying with conventional black box arc model

2015 3rd International Conference on Electric Power Equipment – Switching Technology (ICEPE-ST) ◽

10.1109/icepe-st.2015.7368330 ◽

2015 ◽

Cited By ~ 6

Author(s):

Sung-Woo Lim ◽

Urner Amir Khan ◽

Jogn-Geon Lee ◽

Bang-Wook Lee ◽

Kil-Sou Kim ◽

...

Keyword(s):

Simulation Analysis ◽

Circuit Breaker ◽

Black Box ◽

Arc Model ◽

Dc Arc

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A DC Arc Model for Series Faults in Low Voltage Microgrids

IEEE Transactions on Smart Grid ◽

10.1109/tsg.2012.2201757 ◽

2012 ◽

Vol 3 (4) ◽

pp. 2063-2070 ◽

Cited By ~ 56

Author(s):

Fabian M. Uriarte ◽

Angelo L. Gattozzi ◽

John D. Herbst ◽

Hunter B. Estes ◽

Thomas J. Hotz ◽

...

Keyword(s):

Low Voltage ◽

Arc Model ◽

Dc Arc

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Cascaded HVDC gaseous circuit breaker performance using black box arc model

Electrical Engineering ◽

10.1007/s00202-020-01157-6 ◽

2021 ◽

Author(s):

Osama E. Gouda ◽

Ghada Amer ◽

Mohamed Awaad ◽

Manar Ahmed

Keyword(s):

Circuit Breaker ◽

Black Box ◽

Arc Model

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Simulation of the SF6 Arc Behavior by a Cylindrical Arc Model

IEEE Transactions on Power Apparatus and Systems ◽

10.1109/tpas.1985.319183 ◽

1985 ◽

Vol PAS-104 (7) ◽

pp. 1903-1909 ◽

Cited By ~ 8

Author(s):

T. Tanabe ◽

K. Ibuki ◽

S. Sakuma ◽

T. Yonezawa

Keyword(s):

Arc Model ◽

Arc Behavior

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Feasibility of Black-Box Time Domain Modeling of Single-Phase Photovoltaic Inverters Using Artificial Neural Networks

Energies ◽

10.3390/en14082118 ◽

2021 ◽

Vol 14 (8) ◽

pp. 2118

Author(s):

Elias Kaufhold ◽

Simon Grandl ◽

Jan Meyer ◽

Peter Schegner

Keyword(s):

Time Domain ◽

Single Phase ◽

Low Voltage ◽

Black Box ◽

Steady States ◽

Domain Modeling ◽

Dynamic Simulations ◽

Time Domain Modeling ◽

Artificial Neural ◽

Grid Side

This paper introduces a new black-box approach for time domain modeling of commercially available single-phase photovoltaic (PV) inverters in low voltage networks. An artificial neural network is used as a nonlinear autoregressive exogenous model to represent the steady state behavior as well as dynamic changes of the PV inverter in the frequency range up to 2 kHz. The data for the training and the validation are generated by laboratory measurements of a commercially available inverter for low power applications, i.e., 4.6 kW. The state of the art modeling approaches are explained and the constraints are addressed. The appropriate set of data for training is proposed and the results show the suitability of the trained network as a black-box model in time domain. Such models are required, i.e., for dynamic simulations since they are able to represent the transition between two steady states, which is not possible with classical frequency-domain models (i.e., Norton models). The demonstrated results show that the trained model is able to represent the transition between two steady states and furthermore reflect the frequency coupling characteristic of the grid-side current.

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