DOIONLINE 
DOIONLINE Publish In |
International Journal of Electrical, Electronics and Data Communication (IJEEDC)-IJEEDC |
 Journal Home Volume Issue |
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Issue |
Volume-5,Issue-5 ( May, 2017 ) | |||||||||
Paper Title |
Passive Islanding Detection Method Based on Artificial Neural Network (ANN) Considering Rate of Change of Reactive Power (ROCORP) and Total Harmonic Distortion (THD) | |||||||||
Author Name |
Hasmaini Mohamad, Aimie Nadia Ab Salim, Nofri Yenita Dahlan, Shahrani Shahbudin, Siti Asyran Habibullah | |||||||||
Affilition |
Faculty of Electrical Engineering, Universiti Teknologi Mara, Shah Alam, Selangor | |||||||||
Pages |
10-14 | |||||||||
Abstract |
Distributed generation (DG) technology plays a vital role in power system. Integration of DG in conventional radial distribution system improves the power quality and enhances the power supply capacity. DG integration changes the nature of distribution system from passive to active. Due to this, several technical issues regarding environmental concerns have risen. With regards to this, islanding detection is an important aspect that needs to be considered in order to avoid loss of life and prevent damage to the system. This paper presents a passive islanding detection techniques using Artificial Neural Network (ANN) by considering two parameters which are rate of change of reactive power (ROCORP) and current total harmonic distortion (THDi). PSCAD software is used to simulate the test system for various islanding and non-islanding cases. The data is classified using ANN classifier. The pattern recognition classifier is used and the performance is analysed by using confusion matrix. Results shows that the accuracy of islanding detection is 85.1% and the time taken for the breaker to trip in ANN is much faster. Keywords- Islanding detection; artificial neural network; confusion matrix; rate of change of reactive power; total harmonic distortion | |||||||||
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