IJE TRANSACTIONS B: Applications Vol. 32, No. 2 (February 2019) 240-246    Article in Press

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M. Gholami
( Received: October 21, 2018 – Accepted: January 03, 2019 )

Abstract    Due to the increasing need to distributed energy resources in power systems, their problems should be studied. One the main problem of distributed energy resources is unplanned islanding. The unplanned islanding has some dangers to the power systems and the repairman which are works with the incorrect devices. In this paper, a passive local method is proposed. The proposed method is based on wavelet transform and a new classifier named as wavenet. The wavelet transform is used to extract features from the current waveform of current at the PCC point. PCC is assumed as the connection point of distributed generation to the distribution system. The proposed method is implemented on a 15 bus grid in MATLAB/SIMULINK software. The results show the high accuracy of islanding detection of the proposed method. In this paper, one wind turbine is assumed as a distributed resource.


Keywords    Islanding Detection, Wavelet Transform, Feature Extraction, Wavenet


چکیده    با توجه به افزایش روزافزون استفاده از منابع تولید پراکنده در شبکه‌های قدرت، می‌بایستی مشکلات مربوط به آن مورد توجه بیشتر قرار بگیرند. یکی از مشکلات اصلی جزیره‌ای شدن برنامه‌ریزی نشده است که برای سیستم قدرت و همچنین برای افرادی که با این سیستم کار می‌کنند، خطر ایجاد می‌کند و به همین خاطر مورد مطالعه‌ی بسیاری از محققین قرار گرفته است. در این مقاله یک روش محلی از نوع غیرفعال ارائه شده است. روش ارائه شده برپایه تبدیل موجک و کلاسه‌بندی جدیدی به نام شبکه عصبی موجکی (Wavenet) است. این روش بر روی یک شبکه‌ی 15 باسه در نرم‌افزار MATLAB/SIMULINK پیاده‌سازی شده است. نتایج بدست آمده نشان داده است که روش ارائه شده قادر است با دقت بسیار بالایی جزیره‌ای شدن منبع تولید پراکنده را تشخیص دهد. در این مقاله از توربین بادی به عنوان یک منبع تولید پراکنده استفاده شده است.

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