Towards active distribution networks fault location: Contributions considering DER analytical models and local measurements

Orozco-Henao, C.; Bretãs, Arturo S.; Herrera-Orozco, A.R.; Pulgarín-Rivera, Juan Diego; Dhulipala, Surya Chandan; Wang, S.

doi:10.1016/j.ijepes.2018.01.042

Cited by 27 publications

(24 citation statements)

References 32 publications

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“…For the aforementioned reasons, a fault should be detected, located and isolated as quickly as possible. All three of them are key elements of a self-healing smart grid and they include the following steps: a) detecting the fault usually through threshold crossing detection techniques, b) localizing the fault with any of the five most popular methods [5]: impedance based which are the most widely used [6][7][8], knowledge based [9][10][11], traveling wave [12,13], methods based on sparse measurements [14][15][16] and hybrid methods [17,18] and c) isolating the fault by sending a crew to verify the localization of the fault and fix the problem Due to their increased complexity and the lack of available sensors, the LV distribution grids, have not been on the center of researchers' attention, with few exceptions [7,15,16,19]. The vast majority of the studies focuses on the Medium Voltage (MV) distribution network.…”

Section: Introductionmentioning

confidence: 99%

A Fault Localization Method for Single-Phase to Ground Faults in LV Smart Distribution Grids

Sapountzoglou

Raison

Nuno

2020

Lecture Notes in Electrical Engineering

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Section: Introductionmentioning

confidence: 99%

A Fault Localization Method for Single-Phase to Ground Faults in LV Smart Distribution Grids

Sapountzoglou

Raison

Nuno

2020

Lecture Notes in Electrical Engineering

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“…Another attempt to enhance the accuracy of the classical impedance based method, was made in [5] through the use of voltage measurements obtained from smart meters. Finally, in [6] the current contribution of the inverter-interfaced PV to the fault, was taken into account in the estimation of the fault location.…”

Section: Introductionmentioning

confidence: 99%

“…Besides the promising results that the above methods may present, the vast majority of the studies in literature were focused on low-impedance faults with fault resistance values between 5 mΩ and 50 Ω. Only very few investigated highimpedance fault cases [6], [22]. In addition, up until now and probably because of the complexity they present and the absence of available measurements, there has not been a lot of research around LV distribution grids.…”

Section: Introductionmentioning

confidence: 99%

Fault Detection and Localization in LV Smart Grids

Sapountzoglou

Raison

Silva

2019

2019 IEEE Milan PowerTech

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In this paper, a fault detection and localization method for a Low Voltage (LV) distribution grid are presented. Two fault detection approaches were examined both suitable only for low impedance faults (up to 10 Ω of fault resistance). The first one was based on current measurements at the beginning of the feeder and the second one was based on the highest voltage drop across the feeder branches. The localization method was based solely on nodal rms voltage measurements across the grid. The localization method was divided in three steps: a) faulty branch identification, b) faulty sector localization and c) fault distance estimation. Two categories of faults were examined: single-phase to ground short-circuit (SC) faults and three-phase SC faults. Faults were divided in two major categories: a) faults in the beginning of a branch and b) faults in the middle or towards the end of a branch. Additionally, in order to study the effects of loads and microgeneration units, four different hours in a day were chosen. For all of the above cases both low and high impedance faults were studied with fault resistance values ranging from 0.1 Ω to 1 kΩ. Finally, a preliminary study with less available measurements was made and presented in this paper. The results have been validated by simulation means on a real semi-rural LV distribution network of Portugal.

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“…Some strategies to consider the DER effect on FL have been proposed in the technical literature [16][17][18][19][20][21][22][23][24][25][26][27]. In [16,17,25] the DER effect is considered by using a model of the synchronous machine, which is only valid for INIDER [28].…”

Section: Introductionmentioning

confidence: 99%

“…In [16,17,25] the DER effect is considered by using a model of the synchronous machine, which is only valid for INIDER [28]. In [26,27] the DER effect is considered by using a model of the inverter, which is only valid for IIDER. Further, the methods exposed in the literature [18][19][20][21][22][23][24] are formulated using synchronized current and voltage phasors, provided by Intelligent Electronic Devices (IED), in order to consider the DER effect on the FL.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Impedance-Based Fault Location Algorithm for Active Distribution Networks

et al. 2018

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Modern fault location methods are robust; however, they depend strongly on the availability of the measurements given by Distributed Energy Resources (DER). If the communication or synchronism of this information is lost, the fault location is not possible. This paper proposes an adaptive impedance-based fault location algorithm for active distribution systems. The proposal combines information provided by Intelligent Electronic Devices (IEDs) located at the substation, the knowledge of the network topology and parameters, as well as the distributed power sources, to estimate the fault location. Its adaptive feature is given by the use of a Distributed Energy Resources (DER) electrical model. This model is used to estimate the DER current contribution to the fault, in case the information provided by a local IED is not available. The method takes two types of DER technologies into account: Inverter non-interfaced DER (INIDER) and Inverter-interfaced DER (IIDER). The proposed method is validated on a modified IEEE 34-node test feeder, which was simulated with ATP/EMTP. The results obtained using the IEDs information, presented a maximum error of 0.8%. When this information is not available, the method’s performance decreases slightly, obtaining a maximum error of 1.1%. The proposed method showed better performance when compared with two state of the art methods, indicating potential use for real-life applications.

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Towards active distribution networks fault location: Contributions considering DER analytical models and local measurements

Cited by 27 publications

References 32 publications

A Fault Localization Method for Single-Phase to Ground Faults in LV Smart Distribution Grids

A Fault Localization Method for Single-Phase to Ground Faults in LV Smart Distribution Grids

Fault Detection and Localization in LV Smart Grids

Adaptive Impedance-Based Fault Location Algorithm for Active Distribution Networks

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