Abstract
Due to the existence of different branches in the electricity distribution network and only available of voltage and current information at the beginning of the line and lack of access to the information at the end of the network line, the detection of the faulted section in the distribution network has become more important. Today, smart meters are used to measure the voltage and current of network lines, but due to the limitations of the installation sites, these devices are not possible in all network lines. In this paper, two techniques have been used to identify the faulted section and fault location in the network so that the fault distance at the beginning of the line can be estimated by estimating the current at the end of each network line. Therefore, in this project, by installing smart meters in the main branch of the network and also the information obtained from power flow in the network normal mode, it has been tried to practically estimate the voltage and current at the beginning and end of each distribution network line. In this method, more power flow is used to calculate the voltage drop of the lines and estimate the voltage and current at the end of the network lines so that the faulted part can be identified. Finally, the proposed method is implemented on the IEEE_15bus network, the results of which show the proper performance of the proposed method in estimating location and Fault resistance for different types of faults in the distribution network.
References
Dashtdar, M., Najafi, M., Esmaeilbeig, M.: Calculating the locational marginal price and solving optimal power flow problem based on congestion management using GA-GSF algorithm. Electr. Eng. 102, 1–18 (2020)
Feng, X., Qi, Li., Pan, J.: A novel fault location method and algorithm for DC distribution protection. IEEE Trans. Ind. Appl. 53(3), 1834–1840 (2017)
Valdez, J., Zhang, X., Torres, J.A., Roy, S.: Fast fault location in power transmission networks using transient signatures from sparsely-placed synchrophasors. In: 2014 North American power symposium (NAPS), IEEE, pp. 1–6 (2014).
Choi, M.-S., Lee, S.-J., Lee, D.-S., Jin, B.-G.: A new fault location algorithm using direct circuit analysis for distribution systems. IEEE Trans. Power Deliv. 19(1), 35–41 (2004)
Bahmanyar, A., Estebsari, A., Pons, E., Patti, E., Jamali, S., Bompard, E., Acquaviva, A.: Fast fault location for fast restoration of smart electrical distribution grids. In: 2016 IEEE international smart cities conference (ISC2), IEEE, pp. 1–6 (2016)
Celeita, D., Zambrano, S., Ramos, G.: Fault location framework for distribution systems with DG using DSSim-PC. In: 2014 IEEE PES transmission and distribution conference and exposition-Latin America (PES T&D-LA), IEEE, pp. 1–6 (2014)
de Nunes, J.U.N., Bretas, A.S.: Impedance-based fault location formulation for unbalanced primary distribution systems with distributed generation. In: 2010 International conference on power system technology, IEEE, pp. 1–7 (2010)
Gururajapathy, S.S., Mokhlis, H., AzilIllias, H.: Fault location and detection techniques in power distribution systems with distributed generation: a review. Renew. Sustain. Energy Rev. 74, 949–958 (2017)
Rafinia, A., Moshtagh, J.: A new approach to fault location in a three-phase underground distribution system using a combination of wavelet analysis with ANN and FLS. Int. J. Electr. Power Energy Syst. 55, 261–274 (2014)
Cordova, J., Faruque, M.O.: Fault location identification in smart distribution networks with distributed generation. In: 2015 North American power symposium (NAPS), IEEE, pp. 1–7 (2015)
Dashtdar, M., Dashti, R., Shaker, H.R.: Distribution network fault section identification and fault location using artificial neural network. In: 2018 5th International conference on electrical and electronic engineering (ICEEE), IEEE, pp. 273–278 (2018)
Dashtdar, M.: Fault location in distribution network based on fault current analysis using artificial neural network. Mapta J. Electr. Comput. Eng. 1(2), 18–32 (2018)
Dashtdar, M., Dashtdar, M.: Fault location in the transmission network using a discrete wavelet transform. Am. J. Electr. Comput. Eng. 3(1), 30–37 (2019)
Dashtdar, M., Dashtdar, M.: Fault location in distribution network based on fault current profile and the artificial neural network. Mapta J. Electr. Comput. Eng. 2(1), 30–41 (2020)
Dashtdar, M., Dashtdar, M.: Voltage control in distribution networks in presence of distributed generators based on local and coordinated control structures. Sci. Bull. Electr. Eng. Fac. 19(2), 21–27 (2019)
Dashtdar, M., Dashtdar, M.: Fault location in the transmission network based on extraction of fault components using wavelet transform. Sci. Bull. Electr. Eng. Fac. 19(2), 1–9 (2019)
Dashtdar, M., Dashtdar, M.: Fault location in distribution network based on phasor measurement units (PMU). Sci. Bull. Electr. Eng. Fac. 19(2), 38–43 (2019)
Dashtdar, M., Dashtdar, M.: Detecting the fault section in the distribution network with distributed generators based on optimal placement of smart meters. Sci. Bull. Electr. Eng. Fac. 19(2), 28–34 (2019)
Dashtdar, M., Dashtdar, M.: Fault location in radial distribution network based on fault current profile and the artificial neural network. Sci. Bull. Electr. Eng. Fac. 20(1), 14–21 (2020)
Dashtdar, M., Esmaeilbeig, M., Najafi, M., Bushehri, M.E.N.: Fault location in the transmission network using artificial neural network. Autom. Control Comput. Sci. 54(1), 39–51 (2020)
Dashtdar, M., Esmailbeag, M., Najafi, M.: Fault location in the transmission network based on zero-sequence current analysis using discrete wavelet transform and artificial neural network. Am. J. Electr. Comput. Eng. 3, 30 (2019)
Gohokar, V.N., Khedkar, M.K.: Faults locations in an automated distribution system. Electr. Power Syst. Res. 75(1), 51–55 (2005)
Hosseinimoghadam, S.M.S., Dashtdar, M., Dashtdar, M.: Fault location in distribution networks with the presence of distributed generation units based on the impedance matrix. J. Inst. Eng. India Ser. B (2020). https://doi.org/10.1007/s40031-020-00520-2
Shrestha, M., Johansen, C., Noll, J., Roverso, D.: A methodology for security classification applied to smart grid infrastructures. Int. J. Crit. Infrastruct. Prot. 28, 100342 (2020)
Gord, E., Dashti, R., Najafi, M., Santos, A.Q., Shaker, H.R.: Determining an accurate fault location in electrical energy distribution networks in the presence of DGs using transient analysis. Measurement 151, 107270 (2020)
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Dashtdar, M., Dashtdar, M. Fault location in the distribution network based on scattered measurement in the network. Energy Syst 13, 539–562 (2022). https://doi.org/10.1007/s12667-020-00423-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12667-020-00423-7