Solutions for blinding of protection in today's and future German LV grids with high inverter penetration – simulative and experimental analysis

Glinka, Felix; Schulte, Nicolas; Bertram, Reinhold; Schnettler, Armin; Koprivšek, Mitja

doi:10.1049/joe.2018.0162

Cited by 5 publications

(20 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Given the meshed configuration, fault polarisation is critical as fault detection. Meanwhile, a directional element can be an effective solution to cope with the lower short-circuit currents [59]. Again due to the control functions of inverters, fault polarisation is as challenging as fault detection in microgrids.…”

Section: Fault Polarisationmentioning

confidence: 99%

Trends in the protection of inverter‐based microgrids

Mahamedi

Fletcher

2019

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

Section: Fault Polarisationmentioning

confidence: 99%

Trends in the protection of inverter‐based microgrids

Mahamedi

Fletcher

2019

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

“…Blinding protection areas [5], sympathetic tripping (the false tripping of feeders) [6], and failures of the auto-reclosers [7] are the main challenges that are created by the presence of DG units in distribution networks. Blinding zones cause the relay to operate with a delay or non-tripping [8,9]. Protective relays are not able to detect faults in the blinding mode.…”

Section: Introductionmentioning

confidence: 99%

A Deep GMDH Neural-Network-Based Robust Fault Detection Method for Active Distribution Networks

Çelik,

Farkhani,

Lashab

et al. 2023

Energies

View full text Add to dashboard Cite

The increasing penetration of distributed generation (DG) to power distribution networks mainly induces weaknesses in the sensitivity and selectivity of protection systems. In this manner, conventional protection systems often fail to protect active distribution networks (ADN) in the case of short-circuit faults. To overcome these challenges, the accurate detection of faults in a reasonable fraction of time appears as a critical issue in distribution networks. Machine learning techniques are capable of generating efficient analytical expressions that can be strong candidates in terms of reliable and robust fault detection for several operating scenarios of ADNs. This paper proposes a deep group method of data handling (GMDH) neural network based on a non-pilot protection method for the protection of an ADN. The developed method is independent of the DG capacity and achieves accurate fault detection under load variations, disturbances, and different high-impedance faults (HIFs). To verify the improvements, a test system based on a real distribution network that includes three generators with a capacity of 6 MW is utilized. The extensive simulations of the power network are performed using DIgSILENT Power Factory and MATLAB software. The obtained results reveal that a mean absolute percentage error (MAPE) of 3.51% for the GMDH-network-based protection system is accomplished thanks to formulation via optimized algorithms, without requiring the utilization of any feature selection techniques. The proposed method has a high-speed operation of around 20 ms for the detection of faults, while the conventional OC relay performance is in the blinding mode in the worst situations for faults with HIFs.

show abstract

“…In [18], a whole-line fault analysis method for distribution networks with DGs is proposed, enabling the SCC in faults occurring not only at the location of network buses but also along the lines. In [19], the blinding effects caused on the overcurrent relay of a German low-voltage (LV) feeder are studied, using a tool for stationary short-circuit current calculations, based on the currentsource superposition method. Finally, in [20], the authors study all the problems arising from the connection of DGs to distribution networks, such as blinding, islanding, and miscoordination.…”

Section: Introduction 1motivation and Challengesmentioning

confidence: 99%

“…All the aforementioned SCC methods assume that either all DGs remain connected, injecting a constant current throughout the whole period of the fault, such as in [12][13][14][15][16][17][18][19][20][21][22][23], or they are disconnected once the fault occurs, as in [9][10][11]. Therefore, the short-circuit current is assumed constant, examining only one time instant (snapshot) of the fault.…”

Section: Introduction 1motivation and Challengesmentioning

confidence: 99%

Incorporating Modern Fault Ride-Through Standards into the Short-Circuit Calculation of Distribution Networks

Pompodakis,

Katsigiannis,

Karapidakis

2023

Sensors

View full text Add to dashboard Cite

Modern fault ride-through (FRT) standards in many countries require distributed generators to remain connected for a specified period during the fault by providing reactive current, to support voltage and prevent a massive renewable outage. As a result, short-circuit current is not constant, but it varies depending on the current and disconnection order of distributed generators (DGs). This time-varying short-circuit current complicates the estimation of the time it will take for an overcurrent relay or fuse to trip. The existing short-circuit calculation algorithms usually assume that the fault current is constant throughout the whole period of fault. This assumption may result in incorrect conclusions regarding the tripping time of protective devices in networks with high renewable penetration. This paper incorporates modern FRT standards into the fault analysis by considering the influence of fault current variations on the protective devices (relays, fuses), significantly increasing the accuracy of the estimated tripping time. Simulations carried out in a 13-bus and the IEEE 8500-node network indicate that the traditional short-circuit calculation approaches may miscalculate the tripping time of protective devices, with deviations up to 80 s, when applied to networks complying with modern FRT standards.

show abstract

Solutions for blinding of protection in today's and future German LV grids with high inverter penetration – simulative and experimental analysis

Cited by 5 publications

References 2 publications

Trends in the protection of inverter‐based microgrids

Trends in the protection of inverter‐based microgrids

A Deep GMDH Neural-Network-Based Robust Fault Detection Method for Active Distribution Networks

Incorporating Modern Fault Ride-Through Standards into the Short-Circuit Calculation of Distribution Networks

Contact Info

Product

Resources

About