Multisignal histogram‐based islanding detection using neuro‐fuzzy algorithm |
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| Authors: | Mehrdad Tarafdar Hagh Noradin Ghadimi |
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| Affiliation: | 1. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran;2. Young Researchers and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil, Iran |
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| Abstract: | Islanding is an important concern for grid‐connected distributed resources due to personnel and equipment safety issues. Several techniques based on passive and active detection schemes have been proposed previously. Although passive schemes have a large nondetection zone (NDZ), concerns have been raised about active methods because of their degrading effect on power quality. Reliably detecting this condition is regarded by many as an ongoing challenge because existing methods are not entirely satisfactory. This article proposes a new integrated histogram analysis method using a neuro‐fuzzy approach for islanding detection in grid‐connected wind turbines. The main objective of the proposed approach is to reduce the NDZ to as close as possible to zero and to maintain the output power quality unchanged. In addition, this technique can also overcome the problem of setting detection thresholds which is inherent in existing techniques. The method proposed in this study has a small NDZ and is capable of detecting islanding accurately within the minimum standard time. Moreover, for those regions which require better visualization, the proposed approach can serve as an efficient aid for better detecting grid‐power disconnection. © 2014 Wiley Periodicals, Inc. Complexity 21: 195–205, 2015 |
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| Keywords: | multisignal histogram ANFIS distributed generation islanding detection nondetection zone |
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