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Efficient cloud-based digital-physical testing method for feeder automation system in electrical power distribution network

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A feeder automation (FA) system is usually used by electricity utilities to improve power supply reliability. The FA system was realized by the coordinated control of feeder terminal units (FTUs) in the electrical power distribution network. Existing FA testing technologies can only test basic functions of FTUs, while the coordinated control function among several FTUs during the self-healing process cannot be tested and evaluated. In this paper, a novel cloud-based digital-physical testing method is proposed and discussed for coordinated control capacity test of the FTUs in the distribution network. The coordinated control principle of the FTUs in the local-reclosing FA system is introduced firstly and then, the scheme of the proposed cloud-based digital-physical FA testing method is proposed and discussed. The theoretical action sequences of the FTUs consisting of the FTU under test and the FTUs installed in the same feeder are analyzed and illustrated. The theoretical action sequences are compared with the test results obtained by the realized cloud-based simulation platform and the digital-physical hybrid communication interaction. The coordinated control capacity of the FTUs can be evaluated by the comparative result. Experimental verification shows that the FA function can be tested efficiently and accurately based on our proposed method in the power distribution system inspection.
Rocznik
Strony
545--559
Opis fizyczny
Bibliogr. 15 poz., rys., tab., wz.
Twórcy
autor
  • Guangzhou Power Supply Bureau Co., Ltd China
autor
  • Guangzhou Power Supply Bureau Co., Ltd China
autor
  • Guangzhou Power Supply Bureau Co., Ltd China
autor
  • Guangzhou Power Supply Bureau Co., Ltd China
autor
  • Guangzhou Power Supply Bureau Co., Ltd China
Bibliografia
  • [1] Li Y., Yang R., Zhao X., Reactive power convex optimization of active distribution network based on Improved Grey Wolf Optimizer, Archives of Electrical Engineering, vol. 69, no. 1, pp. 117–131 (2020).
  • [2] Wang P., Chen B., Zhou H. et al., Fault location in resonant grounded network by adaptive control of neutral-to-earth complex impedance, IEEE Transactions on power delivery, vol. 33, no. 2, pp. 689–698 (2018).
  • [3] Fereidunian A., Hosseini M., Talabari M., Toward self-financed distribution automation development: time allocation of automatic switches installation in electricity distribution systems, IET Generation, Transmission and Distribution, vol. 11, no. 3, pp. 3350–3358 (2017).
  • [4] Ling W., Liu D., Yang D. et al., The situation and trends of feeder automation in China, Renewable and Sustainable Energy Reviews, vol. 50, pp. 1138–1147 (2015).
  • [5] Liao C., Ten C., Hu S., Strategic FRTU deployment considering cybersecurity in secondary distribution network, IEEE Transactions on Smart Grid, vol. 4, no. 3, pp. 1264–1274 (2013).
  • [6] Mahdi M., Genc V., A real-time self-healing methodology using model – and measurement-based islanding algorithms, IEEE Transactions on Smart Grid, vol. 10, no. 2, pp. 1195–1204 (2019).
  • [7] Amohadi M., Fotuhi-Firuzabad M., Optimal placement of switching and protection devices in radial distribution networks to enhance system reliability using the AHP-PSO method, Turkish Journal of Electrical Engineering and Computer Sciences, vol. 27, pp. 181–196 (2019).
  • [8] Farajollahi M., Fotuhi-firuzabad M., Safdarian A., Sectionalizing switch placement in distribution networks considering switch failure, IEEE Transactions on Smart Grid, vol. 10, no. 1, pp. 1080–082 (2019).
  • [9] Liu J., Zhang Z., Chen Y. et al., Host injection test technology for fault handling performance test of power distribution network with DG, Automation of Electric Power Systems, vol. 41, no. 13, pp. 119–124, 132 (2017).
  • [10] Alvarez-Herault M., Labonne A., Toure S. et al., An original smart-grids test bed to teach feeder automation functions in a distribution grid, IEEE Transactions on Power Systems, vol. 33, no. 1, pp. 373–385 (2018).
  • [11] Celeita D., Meliopoulos A., Ramos G. et al., Dynamic state estimation for double-end traveling wave arrival identification in transmission lines, Electric Power Systems Research, vol. 170, pp. 138–149 (2019).
  • [12] Zhang Z., Chen Q., Xie R. et al., The fault analysis of PV cable fault in DC microgrids, IEEE Transactions on Energy Conversion, vol. 34, no. 1, pp. 486–496 (2019).
  • [13] Tang J., Xiong B., Yang C. et al., Development of an integrated power distribution system laboratory platform using modular miniature physical elements: a case study of fault location, Energies, vol. 12, p. 3780 (2019).
  • [14] Andreev M., Gusev A., Ruban N. et al., Hybrid real-time simulator of large-scale power systems, IEEE Transactions on Power System, vol. 34, no. 2, pp. 1404–1415 (2019).
  • [15] Song Y., Chen Y., Huang S. et al., Fully GPU-based electromagnetic transient simulation considering large-scale control systems for system-level studies, IET Generation, Transmission and Distribution, vol. 11, no. 11, pp. 2840–2851 (2017).
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-48d52686-8bd3-4509-bd3a-38494f04c833
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