Automatic Faulted Feeder Section Location and Isolation Method for Power Distribution Systems Considering the Change of Topology
Abstract
:1. Introduction
- Novelty 1: The method can automatically recognize the radial networks from the whole distribution systems and transform them into matrix form. This is novel because other methods can only do one of the two parts. Reference [24] can transform the radial network into matrix, but the radial network must be given first. In addition, the method does not give an automatic method to form the matrix. In distribution systems, for the frequent changing of its topology, it is an onerous task to do the two parts manually. The algorithms proposed in [22,23,24,25] can only recognize the topology of the network. Thus, the novel algorithm proposed in this paper is that it can dramatically reduce the required manpower and is not affected by the changes of topology.
- Novelty 2: The method is applicable for multiple faults. It is novel because other methods such as [3,4,5,6,7,8,9,10,11,12,13] do not consider multiple faults. In addition, the authors of [24] state that their method will have limitations when locating multiple faults. Besides, many other methods, such as impedance-based methods [3,4,5,6,7,8] have multi-estimation problem, which should be solved using other skills. The new proposed method does not have this problem.
- Novelty 3: The method can automatically identify the switches that should be opened to isolate the fault after it is located. Methods such as electrical-parameter-based methods [3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,24] can determine the fault point or faulted section only, but cannot give the switches that should be opened to isolate the fault. The importance of this is that there is no need to adopt other methods to isolate the fault. Thus, fault location and isolation are combined in the proposed method.
2. Identification of the Radial Networks
2.1. Form the Network Description Matrix
2.2. Determine the Sets of MDs and Feeder Sections
2.3. Determine the Radial Networks
3. Faulted Feeder Section Location and Isolation
3.1. Form the Fault Information Vector vi for Each Sub-Network
3.2. Determine the Faulted Feeder Section
3.3. Isolation of the Faulted Feeder Section
4. Identification and Isolation of Multiple Faults
- (1)
- Multiple faults occur on different radial networks. For this condition, each fault will be located and isolated independently using the same method as for single faults.
- (2)
- Multiple faults occur on different laterals in the same radial network. For example, for the two faults illustrated in Figure 7, the fault information vector for the faulted radial network under this condition is:
- (3)
- The proposed algorithm can also identify and isolate multiple faults occurring on different feeder sections on the same lateral. Suppose two faults occur in feeder sections ⑤ and ⑥, as shown in Figure 9. The path of the fault in ⑤ is overlapped by that in ⑥.
5. Discussion of the Method
5.1. Operation with Parts of the Network Out of Service
5.2. Improvement of the Method Considering Fault Information Loss
5.3. Cooperation of the Two Parts
6. Case Studies
6.1. Test Case 1: Single Fault in Each Radial Network
6.2. Test Case 2: Simultaneous Faults in Different Laterals in the Same Radial Network
6.3. Test Case 3: Simultaneous Faults in the Same Lateral
6.4. Test Case 4: Fault Location and Isolation Considering Fault Information Loss
6.5.Comparison with Other Method
- (1)
- The proposed method can not only determine the faulted feeder section, but can also give the switches that should be opened to isolate the fault, which is cannot be done by the mentioned comparative methods.
- (2)
- The propose method is not only applicable to single fault, but also to multiple simultaneous faults. The proposed method has no multiple-estimation problem.
- (3)
- Comparing with the mentioned methods, the proposed algorithm does not use any physical or electrical parameters of the feeders. Thus, it is not affected by the fault type or fault/arc resistance, and it can be used on inhomogeneous feeders consisting of sections of both overhead line and underground cable.
7. Conclusions
Author Contributions
Conflicts of Interest
Appendix A
References
- Mora, J.; Cormane, J.; Ordonez, G. K-means algorithm and mixture distributions for locating faults in power systems. Electr. Power Syst. Res. 2009, 79, 714–721. [Google Scholar] [CrossRef]
- Institute of Electrical and Electronics Engineers. IEEE Guide for Determining Fault Location on AC Transmission and Distribution Lines; IEEE Std. C37.114-2004; IEEE: Piscataway, NJ, USA, 2005. [Google Scholar]
- Salim, R.H.; Salim, K.C.O.; Bretas, A.S. Further improvements on impedance-based fault location for power distribution systems. IET Gen. Transm. Distrib. 2011, 5, 467–478. [Google Scholar] [CrossRef]
- Personal, E.; García, A.; Parejo, A.; Larios, D.F.; Biscarri, F.; León, C. A comparison of impedance-based fault location methods for power underground distribution systems. Energies 2016, 9, 1022. [Google Scholar] [CrossRef]
- Liao, Y. Generalized fault-location methods for overhead electric distribution systems. IEEE Trans. Power Del. 2011, 26, 53–64. [Google Scholar] [CrossRef]
- Choi, M.S.; Lee, S.J.; Lim, S.I.; Lee, D.S.; Yang, X. A direct three-phase circuit analysis-based fault location for line-to-line fault. IEEE Trans. Power Del. 2007, 22, 2541–2547. [Google Scholar] [CrossRef]
- Gabr, M.A.; Ibrahim, D.K.; Ahmed, E.S.; Gilany, M.I. A new impedance-based fault location scheme for overhead unbalanced radial distribution networks. Electr. Power Syst. Res. 2017, 142, 153–162. [Google Scholar] [CrossRef]
- Gazzana, D.S.; Ferreira, G.D.; Bretas, A.S.; Carniato, A.; Passos, L.F.N.; Ferreira, A.H.; Silva, J.E.M. An integrated technique for fault location and section identification in distribution systems. Electr. Power Syst. Res. 2014, 115, 65–73. [Google Scholar] [CrossRef]
- Hong, Y.Y.; Wei, Y.H.; Chang, Y.R.; Lee, Y.D.; Liu, P.W. Fault detection and location by static switches in microgrids using wavelet transform and adaptive network-based fuzzy inference system. Energies 2014, 7, 2658–2675. [Google Scholar] [CrossRef]
- Borghetti, A.; Corsi, S.; Nucci, C.A.; Paolone, M.; Peretto, L.; Tinarelli, R. On the use of continuous-wavelet transform for fault location in distribution power systems. Int. J. Electr. Power Energy Syst. 2006, 28, 608–617. [Google Scholar] [CrossRef]
- Borghetti, A.; Boseti, M.; Di Silvestro, M.; Nucci, C.A.; Paolone, M. Continuous-wavelet transform for fault location in distribution power networks: Definition of mother wavelets inferred from fault originated transients. IEEE Trans. Power Syst. 2008, 23, 380–388. [Google Scholar] [CrossRef]
- Orozco-Henao, C.; Bretas, A.S.; Chouhy-Leborgne, R.; Herrera-Orozco, A.R.; Marin-Quintero, J. Active distribution network fault location methodology: A minimum fault reactance and Fibonacci search approach. Int. J. Electr. Power Energy Syst. 2017, 84, 232–241. [Google Scholar] [CrossRef]
- Grajales-Espinal, C.; Mora-Florez, J.; Perez-Londono, S. Advanced fault location strategy for modern power distribution systems based on phase and sequence components and the minimum fault reactance concept. Electr. Power Syst. Res. 2016, 140, 933–941. [Google Scholar] [CrossRef]
- Mokhlis, H.; Haiyu, L.; Khalid, A.R. The application of voltage sags pattern to locate a faulted section in distribution network. Int. Rev. Electr. Eng. 2010, 5, 173–179. [Google Scholar]
- Pereira, R.A.F.; da Silva, L.G.W.; Kezunovic, M.; Mantovani, J.R.S. Improved fault location on distribution feeders based on matching during-fault voltage sags. IEEE Trans. Power Del. 2009, 24, 852–862. [Google Scholar] [CrossRef]
- Lotfifard, S.; Kezunovic, M.; Mousavi, M.J. Voltage sag data utilization for distribution fault location. IEEE Trans. Power Del. 2011, 26, 1239–1246. [Google Scholar] [CrossRef]
- Mokhlis, H.; Li, H. Non-linear representation of voltage sag profiles for fault location in distribution networks. Int. J. Electr. Power Energy Syst. 2011, 33, 124–130. [Google Scholar] [CrossRef]
- Jin, T.; Li, H. Fault location method for distribution lines with distributed generators based on a novel hybrid BPSOGA. IET Gen. Transm. Distrib. 2016, 10, 2454–2643. [Google Scholar] [CrossRef]
- Salim, R.H.; de Oliveira, K.R.C.; Filomena, A.D.; Resener, M.; Bretas, A.S. Hybrid fault diagnosis scheme implementation for power distribution systems automation. IEEE Trans. Power Del. 2008, 23, 1846–1856. [Google Scholar] [CrossRef]
- Aslan, Y.; Yagan, Y.E. Artificial neural-network-based fault location for power distribution lines using the frequency spectra of fault data. Electr. Eng. 2017, 99, 301–311. [Google Scholar] [CrossRef]
- Zhabelova, G.; Vyatkin, V. Multiagent smart grid automation architecture based on IEC 61850/61499 intelligent logical nodes. IEEE Trans. Ind. Electron. 2012, 59, 2351–2362. [Google Scholar] [CrossRef]
- Kashyap, N.; Yang, C.; Sierla, S.; Flikkema, P.G. Automated fault location and isolation in distribution grids with distribution control and unreliable communication. IEEE Trans. Ind. Electron. 2015, 62, 2612–2619. [Google Scholar] [CrossRef]
- Ahuja, A.; Das, S.; Pahwa, A. An AIS-ACO hybrid approach for multi-objective distribution system reconfiguration. IEEE Trans. Power Syst. 2007, 22, 1101–1111. [Google Scholar] [CrossRef]
- Teng, J.H.; Huang, W.H.; Luan, S.W. Automatic and fast faulted line-section location method for distribution systems based on fault indicators. IEEE Trans. Power Syst. 2014, 29, 1653–1662. [Google Scholar] [CrossRef]
- Andrei, H.; Chicco, G. Identification of the radial configurations extracted from the weakly meshed structures of electrical distribution systems. IEEE Trans. Circuits Syst. I Reg. Pap. 2008, 55, 1149–1158. [Google Scholar] [CrossRef]
- Sinngh, R.; Manitsas, E.; Pal, B.C.; Strbac, G. A recursive Bayesian approach for identification of network configuration changes in distribution system state estimation. IEEE Trans. Power Syst. 2010, 25, 1329–1336. [Google Scholar] [CrossRef]
- Sharon, Y.; Annaswamy, A.M.; Motto, A.L.; Chakraborty, A. Topology identification in distribution network with limited measurements. Proceedings of 2012 IEEE Innovative Smart Grid Technologies Conference, Washington, DC, USA, 16–20 January 2012; pp. 1–6. [Google Scholar]
- Zhao, L.; Song, W.Z.; Tong, L.; Wu, Y.; Yang, J. Topology identification in smart grid with limited measurements via convex optimization. In Proceedings of the 2014 IEEE Innovative Smart Grid Technologies-Asia, Kuala Lumpur, Malaysia, 20–23 May 2014; pp. 803–808. [Google Scholar]
- Zorić, K.J.; Djurić, M.B.; Terzija, V. Arcing faults detection on overhead lines from the voltage signal. Int. J. Electr. Power Energy Syst. 1997, 19, 299–303. [Google Scholar] [CrossRef]
- Alamuti, M.M.; Nouri, H.; Ciric, R.M.; Terzija, V. Intermittent fault location in distribution feeders. IEEE Trans. Power Del. 2012, 27, 96–103. [Google Scholar] [CrossRef]
- Radojević, Z.; Terzija, V.; Djurić, M. Multipurpose overhead lines protection numerical algorithm. IEEE Proc. C 1999, 146, 441–446. [Google Scholar]
- Preston, G.; Radojević, Z.M.; Kim, C.H.; Terzija, V. New settings-free fault location algorithm based on synchronized sampling. IET Gen. Transm. Distrib. 2011, 5, 376–383. [Google Scholar] [CrossRef]
- Terzija, V.V.; Koglin, H.J. Long arc in free air: Laboratory testing, modelling, simulation and model-parameters estimation. Generation, Transmission and Distribution. IEE Proc. 2002, 149, 319–325. [Google Scholar]
- Sun, K.M.; Chen, Q.; Zhan, Z.J. An automatic faulted line section location method for electric power distribution systems based on multisource information. IEEE Trans. Power Del. 2016, 31, 1542–1551. [Google Scholar] [CrossRef]
- Das, D. A fuzzy multiobjective approach for network reconfiguration of distribution systems. IEEE Trans. Power Del. 2006, 21, 202–209. [Google Scholar] [CrossRef]
- Tomoiaga, B.; Chindris, M.; Sumper, A.; Villafafila-Robles, R.; Sudria-Andreu, A. Distribution system reconfiguration using genetic algorithm based on connected graphs. Electr. Power Syst. Res. 2013, 104, 216–225. [Google Scholar] [CrossRef]
Fault Position | Open Switches | Fault Position | Open Switches |
---|---|---|---|
⑥ | 6, 7 and 9 | 59 and 60 | |
33 and 34 | 74 and 75 |
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Sun, K.; Chen, Q.; Zhao, P. Automatic Faulted Feeder Section Location and Isolation Method for Power Distribution Systems Considering the Change of Topology. Energies 2017, 10, 1081. https://doi.org/10.3390/en10081081
Sun K, Chen Q, Zhao P. Automatic Faulted Feeder Section Location and Isolation Method for Power Distribution Systems Considering the Change of Topology. Energies. 2017; 10(8):1081. https://doi.org/10.3390/en10081081
Chicago/Turabian StyleSun, Kongming, Qing Chen, and Pu Zhao. 2017. "Automatic Faulted Feeder Section Location and Isolation Method for Power Distribution Systems Considering the Change of Topology" Energies 10, no. 8: 1081. https://doi.org/10.3390/en10081081