Data-Driven Fault Localization in Distribution Systems with Distributed Energy Resources

Lin, Zhidi; Duan, Dongliang; Yang, Qi; Hong, Xuemin; Cheng, Xiang; Yang, Liuqing; Cui, Shuguang

doi:10.3390/en13010275

Cited by 11 publications

(6 citation statements)

References 31 publications

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“…For KDE there are several varieties of bandwidth selectors: plug-in (PI), least squares (or unbiased) cross validation (LSCV or UCV), biased cross validation (BCV), smoothed cross validation (SCV) and normal scale (NS) [50]. Non-parametric data analysis methods have been used, for example, in [51][52][53][54][55][56]. Although the methods for determining the smoothing parameter are well researched and described, their use often requires their proper application.…”

Section: Non-parametric Methods Of Analysing Data On Operation Of Distribution Networkmentioning

confidence: 99%

An Analysis of the Operation of Distribution Networks Using Kernel Density Estimators

Kornatka

Gawlak

2021

Energies

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Efficiency in the operation of distribution networks is one of the commonly recognised goals of the Smart Grid aspect. Novel approaches are needed to assess the level of energy loss and reliability in electricity distribution. Transmission of electricity in the power system is invariably accompanied by certain physical phenomena and random events causing losses. Identifying areas where excessive energy losses or excessive grid failure occur is a key element for energy companies in resource management. The study presented in the article is based on data obtained from distribution system operators concerning 41 distribution regions in Poland for a period of 5 years. The first part of the article presents an analysis of the distribution of values for the introduced energy density and energy losses in the lines of medium- and low-voltage networks and in transformers supplying the low-voltage network. The second part of the article presents the assessment of the network reliability of the same distribution regions based on analysis of the distributions of System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) values for planned and unplanned outages. Data analysis is performed by non-parametric methods by means of kernel estimators.

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Section: Non-parametric Methods Of Analysing Data On Operation Of Distribution Networkmentioning

confidence: 99%

An Analysis of the Operation of Distribution Networks Using Kernel Density Estimators

Kornatka

Gawlak

2021

Energies

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“…SVDD is developed based on SVM theory for the one-class classification. Its goal is to find a smallest hypersphere or domain which can contain all or almost all target samples [23][24][25]. In this paper, the SVDD is briefly described.…”

Section: Support Vector Data Descriptionmentioning

confidence: 99%

Data-Driven Fault Diagnosis for Automotive PEMFC Systems Based on the Steady-State Identification

2021

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Data-driven diagnosis methods for faults of proton exchange membrane fuel cell (PEMFC) systems can diagnose faults through the state variable data collected during the operation of the PEMFC system. However, the state variable data collected from the PEMFC system during the stack switching between different operating points can easily cause false alarms, such that the practical value of the diagnosis system is reduced. To overcome this problem, a fault diagnosis method for PEMFC systems based on steady-state identification is proposed in this paper. The support vector data description (SVDD) and relevance vector machine (RVM) optimized by the artificial bee colony (ABC) are used for the steady-state identification and fault diagnosis. The density-based spatial clustering of applications with noise (DBSCAN) and linear least squares fitting (LLSF) are used to identify the abnormal data in datasets and estimate change rates of the system state variables respectively. The proposed method can automatically identify the state variable data collected from the PEMFC system during the stack switching between different operating points, so that the diagnosis accuracy can be improved and false alarms can be reduced. The proposed method has a certain practical value and can provide a reference for further study.

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“…By substituting the Equations ( 6) and (8) in Equation ( 9), the result of DD for reverse fault condition is obtained as…”

Section: Reverse Fault Conditionmentioning

confidence: 99%

“…Then the reduced data are used to train ANN and SVM for fault detection and classification. In [8], a data‐driven strategy has been proposed to detect faults and identify their locations based on the multi‐level governance regionalization and quantification of the fault detection results in the distribution systems with distributed energy resource (DER). In this strategy, a general criterion has been presented to divide the distribution systems into several subregions based on the division of the network tree to help the hierarchical search for the location of faults.…”

Section: Introductionmentioning

confidence: 99%

Multi‐agent based protection scheme using current‐only directional overcurrent relays for looped/meshed distribution systems

Ataei

Gitizadeh

Lehtonen

et al. 2021

IET Generation Trans & Dist

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The complexity of the design of the protection system using directional over current relays, for modern power distribution systems has been increased due to the looped/meshed operation and the penetration of distributed generations. Finding a reliable and efficient protection scheme that can be easily implemented in these distribution systems is a major challenge. An efficient solution could be the use of artificial intelligent-based multi-agent systems. This paper proposes a novel distributed intelligent based multi-agent protection scheme, which makes use of current-only directional over current relays as agents for detecting and locating faults and isolating faulty areas (lines/busbars) in the distribution systems. All agents can make on-board decisions by exchanging binary data, and do not need a control centre, so the safety of the protection system against one-point failures and cyber-attacks is increased. The proposed scheme does not need to exchange analogue data, and, therefore, it prevents the high bandwidth communication links. Moreover, it is free from the traditional coordination between relays. This scheme is implemented on the IEEE-14 bus and IEEE-30 bus test systems with the distributed generations and several scenarios have been simulated to evaluate its performance.

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Data-Driven Fault Localization in Distribution Systems with Distributed Energy Resources

Cited by 11 publications

References 31 publications

An Analysis of the Operation of Distribution Networks Using Kernel Density Estimators

An Analysis of the Operation of Distribution Networks Using Kernel Density Estimators

Data-Driven Fault Diagnosis for Automotive PEMFC Systems Based on the Steady-State Identification

Multi‐agent based protection scheme using current‐only directional overcurrent relays for looped/meshed distribution systems

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