| Peer-Reviewed

Rotating Machines Based Islanding Detection Using Fuzzy Logic Method Analysis

Received: 11 October 2015     Accepted: 26 October 2015     Published: 13 November 2015
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Abstract

An electric rotating machine can be defined as any form of apparatus which has a rotating member and generates, converts, transforms, or modifies electric power, such as a motor, generator, or synchronous generator. Although there are many variations, the two basic rotating machine types are synchronous and induction machines. The recent increasing use of rotating machines among other distributed generators is due to a number of advantages including peak shaving, improvement of the quality of power and reliability, power efficiency, environmental friendliness among others. Despite the above mentioned benefits of distributed power generation in the power grid, they have one major drawback, unintentional islanding. If this islanding condition is not detected in time or goes undetected, the distributed generator loses synchronism with the rest of the utility supply. This may lead to out of phase reconnection of the two systems and thus destroying the distributed generators and even lead to a total blackout in the power system. Again, upon the occurrence of an island, rotating machine based generators have another possible consequence of self-excitation. There is therefore need of fast detection of islanding condition especially when rotating machine based generators are integrated into the main power grid. There are many islanding detection methods and each has its merits and demerits. Their usage depends on certain factors including type of distributed generation in consideration and cost of implementation. Furthermore, the rotating machine based generators have the capability of sustaining an island. This makes the islanding detection and protection of these generators a bit challenging when compared with inverter based generators. This paper presents a passive islanding detection method, fuzzy logic algorithm, particularly on rotating machine based generators and its results analyzed under different conditions. After this analysis, it is concluded that the proposed method for islanding detection for rotating machine based generators is robust and accurate when implemented in the distribution network. This is because fuzzy logic control helps to improve the interpretability of knowledge-based classifiers through its semantics that provide insight in the classifier structure and decision-making process over crisp classifiers.

Published in International Journal of Energy and Power Engineering (Volume 4, Issue 5)
DOI 10.11648/j.ijepe.20150405.21
Page(s) 311-316
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Fuzzy Logic Control, Rotating Machines, Islanding Detection

References
[1] S. Noradin and G. Behrooz, "Adaptive neuro-fuzzy inference system (ANFIS) islanding detection based on wind turbine simulator," International Journal of Physical sciences, vol. 8, no. 27, pp. 1425-1436, 23 July 2013.
[2] A. Etxegarai, I. Zamora, P. Eguia and L. Valverde, "Islanding detection of synchronous distributed generators," in International Conference on Renewable Energies and Power Quality, spain, 28th to 30th March, 2012.
[3] B. A. Ozeer, G. Hernandez-Gonzalez and T. H. and EL-Fouly, "GuilleDistributed Generation Analysis Case Study 5 – Investigation of Passive Anti-Islanding Detection for Rotating Machine-based DG Technologies," Varennes Research Centre, Canada, 2012.
[4] H. Vahedi, R. Noroozian, A. Jalilvad and G. B. Gharehpetian, "A new method for islanding detection of inverter based distributed generation using DC-link voltage control," IEEE Transaction on power delivery, vol. 26, no. 2, pp. 1176-1186, 2011.
[5] K. M. Shareef, K. H. Reddy and K. S. Kumar, "Islanding detection in Distributed Generation by using Fuzzy Rule based approach," Journal of Electrical and Electronics Engineering, vol. 2, no. 2, pp. 30-36, July-Aug 2012.
[6] B. Bahrani, H. Karimi and R. Iravani, "Non-Detection zone assessment of an active islanding detection method and its experimental evaluation," IEEE transaction on power delivery, vol. 26, no. 2, pp. 517-525, 2011.
[7] M. Bakhshi, R. Noroozian and G. B. Gharehpetian, "Islanding detection of synchronous machine based DGs using average frequency based index," Iranian journal of electrical and eletronic engineering, vol. 9, no. 2, pp. 94-106, June 2013.
[8] S. Samanta, k. El-arroudi, G. Joós and k. I., "A fuzzy rule-based approach for islanding detection in distributed generation," IEEE Transaction on Power Delivery, pp. 1427-33, 2010.
[9] J. Pham, N. Denboer, N. Lidula, G. Member, N. Perera and A. Rajapakse, "Hardware implementation of an islanding detection approach based on current and voltage transients.," Electrical power and energy conference (EPEC), pp. 152-157, 2011.
[10] H. Zeineldin, E. El-Saadany, M. Salama, “AImpact of DG Interface Control on Islanding Detection and Nondetective Zones,” IEEE Trans.on Power Del, vol. 21, no. 3, pp. 1515 – 1523, July 2006.
[11] Pukar Mahat, Zhe Chen, and Birgitte Bak-Jensen,, “Review on islanding operation of distribution system with distributed generation,” International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, Nanjing, China, p. 2743 2748, April 2008.
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  • APA Style

    Lucas Ongondo Mogaka, D. K. Murage, Michael Juma Saulo. (2015). Rotating Machines Based Islanding Detection Using Fuzzy Logic Method Analysis. International Journal of Energy and Power Engineering, 4(5), 311-316. https://doi.org/10.11648/j.ijepe.20150405.21

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    ACS Style

    Lucas Ongondo Mogaka; D. K. Murage; Michael Juma Saulo. Rotating Machines Based Islanding Detection Using Fuzzy Logic Method Analysis. Int. J. Energy Power Eng. 2015, 4(5), 311-316. doi: 10.11648/j.ijepe.20150405.21

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    AMA Style

    Lucas Ongondo Mogaka, D. K. Murage, Michael Juma Saulo. Rotating Machines Based Islanding Detection Using Fuzzy Logic Method Analysis. Int J Energy Power Eng. 2015;4(5):311-316. doi: 10.11648/j.ijepe.20150405.21

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  • @article{10.11648/j.ijepe.20150405.21,
      author = {Lucas Ongondo Mogaka and D. K. Murage and Michael Juma Saulo},
      title = {Rotating Machines Based Islanding Detection Using Fuzzy Logic Method Analysis},
      journal = {International Journal of Energy and Power Engineering},
      volume = {4},
      number = {5},
      pages = {311-316},
      doi = {10.11648/j.ijepe.20150405.21},
      url = {https://doi.org/10.11648/j.ijepe.20150405.21},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20150405.21},
      abstract = {An electric rotating machine can be defined as any form of apparatus which has a rotating member and generates, converts, transforms, or modifies electric power, such as a motor, generator, or synchronous generator. Although there are many variations, the two basic rotating machine types are synchronous and induction machines. The recent increasing use of rotating machines among other distributed generators is due to a number of advantages including peak shaving, improvement of the quality of power and reliability, power efficiency, environmental friendliness among others. Despite the above mentioned benefits of distributed power generation in the power grid, they have one major drawback, unintentional islanding. If this islanding condition is not detected in time or goes undetected, the distributed generator loses synchronism with the rest of the utility supply. This may lead to out of phase reconnection of the two systems and thus destroying the distributed generators and even lead to a total blackout in the power system. Again, upon the occurrence of an island, rotating machine based generators have another possible consequence of self-excitation. There is therefore need of fast detection of islanding condition especially when rotating machine based generators are integrated into the main power grid. There are many islanding detection methods and each has its merits and demerits. Their usage depends on certain factors including type of distributed generation in consideration and cost of implementation. Furthermore, the rotating machine based generators have the capability of sustaining an island. This makes the islanding detection and protection of these generators a bit challenging when compared with inverter based generators. This paper presents a passive islanding detection method, fuzzy logic algorithm, particularly on rotating machine based generators and its results analyzed under different conditions. After this analysis, it is concluded that the proposed method for islanding detection for rotating machine based generators is robust and accurate when implemented in the distribution network. This is because fuzzy logic control helps to improve the interpretability of knowledge-based classifiers through its semantics that provide insight in the classifier structure and decision-making process over crisp classifiers.},
     year = {2015}
    }
    

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  • TY  - JOUR
    T1  - Rotating Machines Based Islanding Detection Using Fuzzy Logic Method Analysis
    AU  - Lucas Ongondo Mogaka
    AU  - D. K. Murage
    AU  - Michael Juma Saulo
    Y1  - 2015/11/13
    PY  - 2015
    N1  - https://doi.org/10.11648/j.ijepe.20150405.21
    DO  - 10.11648/j.ijepe.20150405.21
    T2  - International Journal of Energy and Power Engineering
    JF  - International Journal of Energy and Power Engineering
    JO  - International Journal of Energy and Power Engineering
    SP  - 311
    EP  - 316
    PB  - Science Publishing Group
    SN  - 2326-960X
    UR  - https://doi.org/10.11648/j.ijepe.20150405.21
    AB  - An electric rotating machine can be defined as any form of apparatus which has a rotating member and generates, converts, transforms, or modifies electric power, such as a motor, generator, or synchronous generator. Although there are many variations, the two basic rotating machine types are synchronous and induction machines. The recent increasing use of rotating machines among other distributed generators is due to a number of advantages including peak shaving, improvement of the quality of power and reliability, power efficiency, environmental friendliness among others. Despite the above mentioned benefits of distributed power generation in the power grid, they have one major drawback, unintentional islanding. If this islanding condition is not detected in time or goes undetected, the distributed generator loses synchronism with the rest of the utility supply. This may lead to out of phase reconnection of the two systems and thus destroying the distributed generators and even lead to a total blackout in the power system. Again, upon the occurrence of an island, rotating machine based generators have another possible consequence of self-excitation. There is therefore need of fast detection of islanding condition especially when rotating machine based generators are integrated into the main power grid. There are many islanding detection methods and each has its merits and demerits. Their usage depends on certain factors including type of distributed generation in consideration and cost of implementation. Furthermore, the rotating machine based generators have the capability of sustaining an island. This makes the islanding detection and protection of these generators a bit challenging when compared with inverter based generators. This paper presents a passive islanding detection method, fuzzy logic algorithm, particularly on rotating machine based generators and its results analyzed under different conditions. After this analysis, it is concluded that the proposed method for islanding detection for rotating machine based generators is robust and accurate when implemented in the distribution network. This is because fuzzy logic control helps to improve the interpretability of knowledge-based classifiers through its semantics that provide insight in the classifier structure and decision-making process over crisp classifiers.
    VL  - 4
    IS  - 5
    ER  - 

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Author Information
  • Electrical and Electronics Department, Technical University of Mombasa, Mombasa, Kenya

  • Electrical and Electronics Department, JKUAT, Nairobi, Kenya

  • Electrical and Electronics Department, Technical University of Mombasa, Mombasa, Kenya

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