RESEARCH PAPER
Fault diagnosis and identification in the distribution network using the fuzzy expert system
| 1 | HEP ODS Elektroslavonija Osijek Cara Hadrijana 3, 31000 Osijek, Croatia |
| 2 | Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering, Computer Science and Information Technology Osijek Kneza Trpimira 2B 31000 Osijek, Croatia |
Publication date: 2018-12-31
Eksploatacja i Niezawodność – Maintenance and Reliability 2018;20(4):621–629
KEYWORDS
ABSTRACT
In this paper, a fuzzy expert off-line system has been developed for fault diagnosis in the distribution network based on the structural and functional operation of the relay and circuit breakers. Functional operations (correct operation, false operation and
failure to operate) of the relays and circuit breakers are described by fuzzy logic. Input data for the proposed fuzzy expert fault diagnosis system (FDS) are status and time stamps of the alarms, associated with relays and circuit breakers. The diagnostic system
from a huge number of alarms sets, logically organizes and quantifies the diagnosis. FDS can diagnose correct operation, false
operation and failure to operate of the relays and circuit breakers. Also, it can identify and quantify fault location based on the
Hamacher’s operator of a fuzzy union. The additional contribution of this paper is in modeling unknown information using linear
fuzzy membership function. Statuses of certain components may be unknown due to telemetry failures or are simply unavailable to
the operator and proposed FDS can make diagnosis in such a situation. Developed fuzzy expert FDS is tested on the two examples
of faults in real life distribution network
REFERENCES (38)
1.
Amiri F, Khadivar A. A fuzzy expert system for diagnosis and treatment of musculoskeletal disorders in wrist. Tehnicki vjesnik – Technical Gazette 2017; 24(1): 147-155.
2.
Bedekar P P, Bhide S R, Kale V S. Fault section estimation in power system using Hebb's rule and continuous genetic algorithm. International Journal of Electrical Power & Energy Systems 2011; 33: 457–465, https://doi.org/10.1016/j.ijep....
3.
Bi T, Wen F, Ni Y, Wu F F. Distributed fault section estimation system using radial basis function neural network and its companion fuzzy system. International Journal of Electrical Power & Energy Systems 2003; 25(5): 377–386, https://doi.org/10.1016/S0142-....
4.
Chang C S, Chen J M, Srinivasan D, Wen F S, Liew A C. Fuzzy logic approach in power system fault section identification. IEE Proceedings - Generation, Transmission and Distribution 1997; 144(5): 406-414, https://doi.org/10.1049/ip-gtd....
5.
Daniels M J, Hogan J W. Missing data in longitudinal studies: Strategies for Bayesian Modeling and Sensitivity Analysis, Chapman & Hall/CRC, 2008.
6.
Duan R, Hu L, Lin Y. Fault diagnosis for complex systems based on dynamic evidential network and multi-attribute decision making with interval numbers. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2017; 19(4): 580–589, https://doi.org/10.17531/ein.2....
7.
Ferreira V H, Zanghi R, Fortes M Z, Sotelo G G, Silva R B M, Souza J C S, Guimarães C H C, Gomes S. A survey on intelligent system application to fault diagnosis in electric power system transmission lines. Electric Power Systems Research 2016; 136: 135–153, https://doi.org/10.1016/j.epsr....
8.
Gómez Mu-oz C, García Marquez F, Arcos Jimenez A, Cheng L, Kogia M, Mohimi A, Papaelias M. A heuristic method for detecting and locating faults employing electromagnetic acoustic transducers. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2017; 19(4): 493–500, https://doi.org/10.17531/ein.2....
9.
Hyun-Joon C, Jong-Keun P. An expert system for fault section diagnosis of power systems using fuzzy relations. IEEE Transactions on power systems 1997; 12(1): 342-348, https://doi.org/10.1109/59.574....
10.
Isik M F, Haboglu M R, Yilmaz C, Yilmaz E N. Design and Implementation of Real Time Monitoring and Control System for Distributed Robotic Systems Supported with IOS/Android Application. Tehnicki vjesnik - Technical Gazette 2018; 25(2): 423-428.
11.
Jadid S B, Jeyasurya B, Khaparde S A. Power system fault diagnosis expert system using PROLOG. Fourth IEEE Region 10 International Conference TENCON, IEEE; 778–781, https://doi.org/10.1109/TENCON....
12.
Jarventausta P, Verho P, Partanen J. Using fuzzy sets to model the uncertainty in the fault location process of distribution networks. IEEE Transactions on Power Delivery 1994; 9(2): 954–960, https://doi.org/10.1109/61.296....
13.
Kimura T, Nishimatsu S, Ueki Y, Fukuyama Y. Development of an expert system for estimating fault section in control center based on protective system simulation. IEEE Transactions on Power Delivery 1992; 7(1): 167–172, https://doi.org/10.1109/61.108....
14.
Leão F B, Pereira R A F, Mantovani J R S. Fast fault section estimation in distribution control centers using adaptive genetic algorithm. International Journal of Electrical Power & Energy Systems 2014; 63: 787–805, https://doi.org/10.1016/j.ijep....
15.
Lee H-J, Park D-Y, Bok-Shin Ahn, Park Y-M, Park J-K, Venkata S S. A fuzzy expert system for the integrated fault diagnosis. IEEE Transactions on Power Delivery 2000; 15(2): 833–838, https://doi.org/10.1109/61.853....
16.
Liacco T E, Kraynak T J. Processing by logic programming of circuit-breaker and protective-relaying information. IEEE Transactions on power apparatus and systems 1969; 88(2): 171-175, https://doi.org/10.1109/TPAS.1....
17.
Liao Z, Wang D, Tang L, Ren J, Liu Z. A Heuristic Diagnostic Method for a PV System: Triple-Layered Particle Swarm Optimization–Back Propagation Neural Network. Energies 2017; 10(2): 226, https://doi.org/10.3390/en1002....
18.
McDonald J R, Burt G M, Zielinski J S, McArthur S D J. Intelligent knowledge based systems in electrical power engineering. Boston, MA: Springer US; 1997, https://doi.org/10.1007/978-1-....
19.
Meza E M, de Souza J C S, Schilling M T, Do Coutto Filho M B. Exploring fuzzy relations for alarm processing and fault location in electrical power systems. 2001 IEEE Porto Power Tech Proceedings, https://doi.org/10.1109/PTC.20....
20.
Monsef H, Ranjbar A M, Jadid S. Fuzzy rule-based expert system for power system fault diagnosis. IEE Proceedings - Generation, Transmission and Distribution 1997; 144(2); 186-192, https://doi.org/10.1049/ip-gtd....
21.
Oliveira A L, de Araújo O C B, Cardoso G, de Morais A P, Mariotto L. A mixed integer programming model for optimal fault section estimation in power systems. International Journal of Electrical Power & Energy Systems 2016; 77: 372–384, https://doi.org/10.1016/j.ijep....
22.
Park Y M, Kim G W, Sohn J M. A logic based expert system (LBES) for fault diagnosis of power system. IEEE Transactions on power systems 1997; 12(1): 363-369, https://doi.org/10.1109/59.574....
23.
Pospiech_Kurkowska S. Processing of Missing Data in a Fuzzy System. In: Pietka E, Kawa J (editors). Information Technologies in Biomedicine. Advances in Soft Computing 2008; 47.
24.
Rafinia A, Moshtagh J. A new approach to fault location in three-phase underground distribution system using combination of wavelet analysis with ANN and FLS. International Journal of Electrical Power & Energy Systems 2014; 55: 261–274, https://doi.org/10.1016/j.ijep....
25.
Rahman M S, Isherwood N, Oo A M T. Multi-agent based coordinated protection systems for distribution feeder fault diagnosis and reconfiguration. International Journal of Electrical Power & Energy Systems 2018; 97:106–119, https://doi.org/10.1016/j.ijep....
26.
Sekine Y, Akimoto Y, Kunugi M, Fukui C, Fukui S. Fault diagnosis of power systems. Proceedings of the IEEE 1992; 80(5): 673–683, https://doi.org/10.1109/5.1372....
27.
Shrivastava S, Jain S, Nema R K, Chaurasia V. Two level islanding detection method for distributed generators in distribution networks. International Journal of Electrical Power & Energy Systems 2017; 87: 222–231, https://doi.org/10.1016/j.ijep....
28.
Smolinski M, Perkowski T, Mystkowski A, Egidijus D, Eidukynas D, Jastrzebski R P. AMB flywheel integration with photovoltaic system for household purpose. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2017; 19(1): 86–94, https://doi.org/10.17531/ein.2....
29.
Talukdar S N, Cardozo E, Leao Luiz V. Toast: The Power System Operator's Assistant. Computer 1986; 19(7): 53–60, https://doi.org/10.1109/MC.198....
30.
Topić D, Šljivac D, Stojkov M. Reliability model of different wind power plant configuration using sequential monte carlo simulation. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2016; 18(2): 237–244, https://doi.org/10.17531/ein.2....
31.
Wall de T, Pannekoke J, Scholtus S. Handbook of statistical data editing and imputation, Wiley, 2011.
32.
Wollenberg B F, Sakaguchi T. Artificial intelligence in power system operations. Proceedings of the IEEE 1987; 75(12): 1678–1685, https://doi.org/10.1109/PROC.1....
33.
Yu D, Chen Z M, Xiahou K S, Li M S, Ji T Y, Wu Q H. A radically data-driven method for fault detection and diagnosis in wind turbines. International Journal of Electrical Power & Energy Systems 2018; 99: 577–584, https://doi.org/10.1016/j.ijep....
34.
Zhang Y, Zhang Y, Wen F, Chung C Y, Tseng C-L, Zhang X, Zeng F, Yuan Y. A fuzzy Petri net based approach for fault diagnosis in power systems considering temporal constraints. International Journal of Electrical Power & Energy Systems 2016; 78: 215–224, https://doi.org/10.1016/j.ijep....
35.
Zhao Y, Li D, Dong A, Kang D, Lv Q, Shang L. Fault Prediction and Diagnosis of Wind Turbine Generators Using SCADA Data. Energies 2017; 10(8): 1210, https://doi.org/10.3390/en1008....
36.
Zhou Q, Xiong T, Wang M, Xiang C, Xu Q. Diagnosis and Early Warning of Wind Turbine Faults Based on Cluster Analysis Theory and Modified ANFIS. Energies 2017; 10(7): 898, https://doi.org/10.3390/en1007....
37.
Zimmermann H J. Fuzzy Set Theory—and Its Applications, Fourth Edition. New York: Springer Science+Business Media, 2001.
38.
Kaluđer S, Nikolovski S, Majdandžić Lj. Alarm processing in a power system by human expert. Tehnicki vjesnik - Technical Gazette 2013; 20(2): 343-349.Re.
CITATIONS (9):
1.
The Concept of Using an Expert System and Multi-Valued Logic Trees to Assess the Energy Consumption of an Electric Car in Selected Driving Cycles
Adam Deptuła, Andrzej Augustynowicz, Michał Stosiak, Krzysztof Towarnicki, Mykola Karpenko
Energies
Adam Deptuła, Andrzej Augustynowicz, Michał Stosiak, Krzysztof Towarnicki, Mykola Karpenko
Energies
2.
Fault Location Method for Active Distribution Network Based on SVM and Feature Search Algorithm
Jia Wei, Shiwu Xiao, Weijie Dong
2019 IEEE 3rd International Electrical and Energy Conference (CIEEC)
Jia Wei, Shiwu Xiao, Weijie Dong
2019 IEEE 3rd International Electrical and Energy Conference (CIEEC)
3.
Analysis of Cable Screen Currents for Diagnostics Purposes
Krzysztof Lowczowski, Zbigniew Nadolny, Bartosz Olejnik
Energies
Krzysztof Lowczowski, Zbigniew Nadolny, Bartosz Olejnik
Energies
4.
Entropy Weight-Logarithmic Fuzzy Multiobjective Programming Method for Evaluating Emergency Evacuation in Crowded Places: A Case Study of a University Teaching Building
Zhian Huang, Wei Zhao, Zhenlu Shao, Yukun Gao, Yinghua Zhang, Ziyou Li, Jinyang Li, Qian Xixi
IEEE Access
Zhian Huang, Wei Zhao, Zhenlu Shao, Yukun Gao, Yinghua Zhang, Ziyou Li, Jinyang Li, Qian Xixi
IEEE Access
5.
Dynamic Analysis Method for Fault Propagation Behaviour of Machining Centres
Liming Mu, Yingzhi Zhang, Jintong Liu, Fenli Zhai, Jie Song
Applied Sciences
Liming Mu, Yingzhi Zhang, Jintong Liu, Fenli Zhai, Jie Song
Applied Sciences
6.
A Review on Fault Diagnosis Technology of Key Components in Cold Ironing System
Kai Ding, Chen Yao, Yifan Li, Qinglong Hao, Yaqiong Lv, Zengrui Huang
Sustainability
Kai Ding, Chen Yao, Yifan Li, Qinglong Hao, Yaqiong Lv, Zengrui Huang
Sustainability
7.
Universal Transparent Artificial Neural Network‐Based Fault Section Diagnosis Models for Power Systems
Xuan Xie, Guojiang Xiong, Jun Chen, Jing Zhang
Advanced Theory and Simulations
Xuan Xie, Guojiang Xiong, Jun Chen, Jing Zhang
Advanced Theory and Simulations
8.
Modified convolutional neural network with global average pooling for intelligent fault diagnosis of industrial gearbox
Yaxin Li, Kesheng Wang
Eksploatacja i Niezawodność – Maintenance and Reliability
Yaxin Li, Kesheng Wang
Eksploatacja i Niezawodność – Maintenance and Reliability
9.
Fault diagnosis of multistage centrifugal pump unit using non-local means-based vibration signal denoising
Te Han, Dongxiang Jiang
Eksploatacja i Niezawodność – Maintenance and Reliability
Te Han, Dongxiang Jiang
Eksploatacja i Niezawodność – Maintenance and Reliability
RELATED ARTICLE
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.