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A New Islanding Detection Method Based on Wavelet-transform and ANN for Micro-grid Including Inverter Assisted Distributed Generator

  • Zhengyuan Guan and Yuan Liao ORCID logo EMAIL logo
Published/Copyright: October 15, 2019

Abstract

This paper presents a new composite approach based on wavelet-transform and ANN for islanding detection of distributed generation (DG). The proposed method first uses wavelet-transform to detect the occurrence of events, and then uses artificial neural network (ANN) to classify islanding and non-islanding events. Total harmonic distortion and voltage unbalance are extracted as feature inputs for ANN classifier. The performance of the proposed method is tested by simulations for two typical distribution networks based on MATLAB/Simulink. The results show that the developed method can effectively detect islanding with low misclassification. The method has the advantages of small non-detection zone and robustness against noises.

References

[1] IEEE Standard 1574. IEEE standard for interconnecting distributed resources into electric power systems, June 2003.Search in Google Scholar

[2] Mohamed EA, Mitani Y. Enhancement the dynamic performance of islanded microgrid using a coordination of frequency control and digital protection. Int J Emerging Electr Power Syst. 2019;20. DOI: 10.1515/ijeeps-2018-0136.Search in Google Scholar

[3] Jing M, Chao M, Zengping W. A novel islanding detection method based on positive feedback of voltage harmonic distortion. Autom Electr Power Syst. 2012;36:47–9.Search in Google Scholar

[4] Jang SI, Kim KH. An islanding detection method for distributed generations using voltage unbalance and total harmonic distortion of current. IEEE Trans Power Delivery. 2004;19:745–52.10.1109/TPWRD.2003.822964Search in Google Scholar

[5] Xu W, Zhang G, Li C, Wang W, Wang G, Kliber J. A power line signaling based technique for anti-islanding protection of distributed generators-part I: scheme and analysis. IEEE Trans Power Delivery. 2007;22:1758–66.10.1109/TPWRD.2007.899618Search in Google Scholar

[6] Liao Y, Turner M, Yan D. Development of a smart-grid roadmap for Kentucky. Electric Power Compon Syst. 2014;42:267–79.10.1080/15325008.2013.862320Search in Google Scholar

[7] Bozoki B. Effects of noise on transfer-trip carrier relaying. IEEE Trans Power Apparatus Syst. 1968;87:173–9.10.1109/TPAS.1968.292268Search in Google Scholar

[8] Smith GA, Onions PA, Infield DG. Predicting islanding operation of grid connected pv inverters. IEEE Proc Electr Power Appl. 2000;147:1–6.10.1049/ip-epa:20000004Search in Google Scholar

[9] Ropp ME, Begovic M, Rohatgi A. Analysis and performance assessment of the active frequency drift method of islanding prevention. IEEE Tran Energy Convers. 1999;14:810–6.10.1109/60.790956Search in Google Scholar

[10] Freitas W, Xu W, Affonso CM, Huang Z. Comparative analysis between ROCOF and vector surge relays for distributed generation applications. IEEE Trans Power Del. 2005;20:1315–24.10.1109/TPWRD.2004.834869Search in Google Scholar

[11] Hung G, Chang C, Chen C. Automatic phase-shift method for islanding detection of grid-connected photovoltaic inverter. IEEE Trans Energy Convers. 2003;18:169–73.10.1109/TEC.2002.808412Search in Google Scholar

[12] Samui A, Samantaray SR. Assessment of ROCPAD Relay for islanding detection in distributed generation. IEEE Trans Smartgrid. 2011;2:391–8.10.1109/TSG.2011.2125804Search in Google Scholar

[13] Nale R, Biswal M. Comparative assessment of passive islanding detection techniques for microgrids. In: Proc. IEEE Conference on Innovations in Information, Embedded and Communication system (ICIIECS-2017), Coimbatore, 17–18 March, 2017.10.1109/ICIIECS.2017.8275935Search in Google Scholar

[14] Nale R, Biswal M. Islanding detection in distribution generation system using intrinsic time decomposition. IET Gener Transm Distrib. 2019;13:626–33.10.1049/iet-gtd.2018.5645Search in Google Scholar

[15] Kunte RS. A wavelet transform-based islanding detection algorithm for inverter assisted distributed generations. M.S. Thesis, Vols. Tennessee Technological University, TN, p. ECE, 2009.Search in Google Scholar

[16] Dwivedi UD, Singh SN. De-noising techniques with change point approach for wavelet-based power quality monitoring. IEEE Trans Power Delivery. 2009;24:1719–27.10.1109/TPWRD.2009.2022665Search in Google Scholar

[17] Dwivedi UD, Singh SN, Srivastava SC. A wavelet based approach for classification and location of faults in distribution systems. IEEE Conf Exhibition Control Commun Autom. 2008;2:488–93.10.1109/INDCON.2008.4768772Search in Google Scholar

[18] Daubechies J. The wavelet transforms, time frequency localization and signal analysis. IEEE Trans IT. 1990;36:961–1005.10.1109/18.57199Search in Google Scholar

[19] Siddique A, Yadava GS, Singh B. Effects of voltage unbalance on induction motors. In: Conference Record of the 2004 IEEE International Symposium on Electrical Insulations, Indianapolis,IN, USA, 2004.Search in Google Scholar

[20] Blagouchine I, Moreau E. Analytic method for the computation of the total harmonic distortion by the cauchy method of residues. IEEE Trans Commun. 2011;59:2478–91.10.1109/TCOMM.2011.061511.100749Search in Google Scholar

[21] Liao Y. A novel method for locating faults on distribution networks. Electr Power Syst Res. 2014;117:21–6.10.1016/j.epsr.2014.07.026Search in Google Scholar

Received: 2019-04-04
Revised: 2019-08-27
Accepted: 2019-09-22
Published Online: 2019-10-15

© 2019 Walter de Gruyter GmbH, Berlin/Boston

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