Fault Detection and Location Method for Mesh-Type DC Microgrid Using Pearson Correlation Coefficient

Kong, Liang; Nian, Heng

doi:10.1109/tpwrd.2020.3008924

Cited by 92 publications

(26 citation statements)

References 23 publications

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“…The protection of DC systems is widely studied in recent research works, and the suggested methods can be categorized as fault detection, [5]- [7], and fault location schemes [8]- [10].…”

Section: A Related Workmentioning

confidence: 99%

“…To improve the reliability of protection systems, in [7], a backup protection system is suggested and uses a sequential analyzing technique. On the other hand, the fault location techniques in recent studies use an additional fault location module [8], the slope of fault current [9], and the Pearson correlation coefficient [10]. However, the existing works cannot accurately locate the high-impedance faults in meshed configuration DC systems without using communication links or additional equipment, which increases the cost of the protection system or reduces the reliability of the entire system.…”

Section: Local Fault Location In Meshed DC Microgrids Based On Parameter Estimation Techniquementioning

confidence: 99%

“…To the best of the author's knowledge, the proposed scheme has the highest accuracy and lowest cost among the existing local fault location systems [8]- [10] for DC microgrids. The differences between DC and AC, meshed and radial microgrids, and with or without communication link in protection systems lead to the following challenges which are addressed in this work:…”

Section: B Contribution Of Researchmentioning

confidence: 99%

“…[9] Accurate, specified for constant power loads at DC Microgrids, and suitable for high impedance faults Only can be implemented in radial systems, and can locate faults in a constant power load array system [10] Fast, accurate, and applicable in both mesh and radial systems Requiring high sampling rate, and analysing data in different windows.…”

Section: A Fault Characteristics In DC Microgridsmentioning

confidence: 99%

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Local Fault Location in Meshed DC Microgrids Based On Parameter Estimation Technique

Bayati

Baghaee

Hajizadeh

et al. 2022

IEEE Systems Journal

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Accurate locating of the faulty section is desired in DC microgrid due to the presence of power electronic converters and low-impedance cables. Some of the existing schemes consider power sources at only one end of the line; thus, assume that the fault current is injected from only one end of the line. This assumption is not true in the case of meshed DC microgrids, where fault current would be supplied from both ends. Moreover, existing communication-based methods require either a fast communication network or data synchronization. To address the aforementioned issues, this paper proposes a novel local fault location scheme for meshed DC microgrids. Low-and highimpedance faults are located by measuring the current by localized intelligent electronic device (LIED). Based on the parameter estimation approach, the fault location is estimated by sampling the peak values of the fault current. The effectiveness of the proposed strategy is evaluated based on offline digital timedomain simulations in MATLAB/Simulink software environment for a meshed test microgrid system and experimentally verified by implementing in a laboratory-scale hardware setup. Comparing the proposed method with other existing methods proves the effectiveness of the proposed technique for different types of faults.

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“…The protection of DC systems is widely studied in recent research works, and the suggested methods can be categorized as fault detection, [5]- [7], and fault location schemes [8]- [10].…”

Section: A Related Workmentioning

confidence: 99%

Section: Local Fault Location In Meshed DC Microgrids Based On Parameter Estimation Techniquementioning

confidence: 99%

Section: B Contribution Of Researchmentioning

confidence: 99%

Section: A Fault Characteristics In DC Microgridsmentioning

confidence: 99%

See 2 more Smart Citations

Local Fault Location in Meshed DC Microgrids Based On Parameter Estimation Technique

Bayati

Baghaee

Hajizadeh

et al. 2022

IEEE Systems Journal

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“…Meanwhile, the faulty currents and nodes voltages obtained by the transient modeling can be used as reference signals compared with the sampled signals in fault location. The use in fault detection and fault location can be found in [26]. While, the use for the selection of parameters of isolation devices can be found in [27].…”

Section: Enable Isolation Devices Normal Operationmentioning

confidence: 99%

Transient Modeling Method for Faulty DC Microgrid Considering Control Effect of DC/AC and DC/DC Converters

Kong

Nian

2020

IEEE Access

Self Cite

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The accurate transient modeling of faulty DC microgrids is the basis of fault detection, fault location and fault isolation. AC/DC and DC/DC converters keeps their normal control strategies until the fault is detected. However, in existing researches, the influence of the control effect of converters is normally being ignored in the transient characteristics of DC microgrids. This omission reduces the accuracy of the faulty transient model. Thus, this paper proposes a transient modeling method for faulty DC microgrid considering control effect of different DC/AC and DC/DC converters. Firstly, the transient characteristics of different converters (including voltage source converter, boost circuit, bidirectional chopper circuit and buck circuit) are analyzed. And then, the faulty transient model of ring-type DC microgrid is established. Furthermore, the correctness of proposed modeling method is verified by comparing with the Control-hardware-in-loop (CHIL) test system. The results show that the proposed method can not only improve the accuracy of transient analysis of faulty DC microgrid, but also enhance the calculation efficiency.INDEX TERMS DC microgrid, Faulty transient modeling, Control effect, Converter.

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An enhanced DPCA fault diagnosis method based on hierarchical cluster analysis

Chen,

Bai,

Zou

2023

Can J Chem Eng

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A large amount of data generated in industrial processes exhibit multi‐modal, nonlinear, time‐domain correlation, and other characteristics. This poses great difficulty for the traditional principal component analysis (PCA) method since it requires that the input data need to conform to the Gaussian distribution. However, the data may have autocorrelation, that is, the data at the current moment will be affected by the past data. To this end, this paper proposes an enhanced dynamic principal component analysis (DPCA) method based on hierarchical clustering analysis. On the basis of the DPCA algorithm, the idea of data classification and enhanced training is used to strengthen the training of the dimensionality reduction matrix. Then, calibration, on‐line monitoring, and fault diagnosis of process data can be conducted. Finally, this paper demonstrates that the performance of the proposed method is greatly improved compared with PCA and DPCA through the Tennessee Eastman process system.

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Fault Detection and Location Method for Mesh-Type DC Microgrid Using Pearson Correlation Coefficient

Cited by 92 publications

References 23 publications

Local Fault Location in Meshed DC Microgrids Based On Parameter Estimation Technique

Local Fault Location in Meshed DC Microgrids Based On Parameter Estimation Technique

Transient Modeling Method for Faulty DC Microgrid Considering Control Effect of DC/AC and DC/DC Converters

An enhanced DPCA fault diagnosis method based on hierarchical cluster analysis

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