2
Transmission and Distribution Department, Electric Power Research Institute
3
Electerical Engineering, Amirkabir University of Technology
Abstract
Accurate models of Overcurrent (OC) with inverse time relay characteristics play an important role for coordination of power system protection schemes. This paper proposes a new method for modeling OC relays curves. The model is based on fuzzy logic and artificial neural networks. The feed forward multilayer perceptron neural network is used to calculate operating times of OC relays for various Time Dial Settings (TDS) or Time Multiplier Settings (TMS). The new model is more accurate than traditional models. The model is validated by comparing the results obtained from the new method with linear and nonlinear Sachdev models as applied for various types of overcurrent relays.
Al-Dabbagh Hossein, M., Heidari, G., Askarian Abyaneh, H., & K. Karegar, H. (2003). A Novel Fuzzy and Artificial Neural Network Representation of Overcurrent Relay Characteristics. International Journal of Engineering, 16(3), 233-246.
MLA
M. Al-Dabbagh Hossein; G. Heidari; H. Askarian Abyaneh; H. K. Karegar. "A Novel Fuzzy and Artificial Neural Network Representation of Overcurrent Relay Characteristics". International Journal of Engineering, 16, 3, 2003, 233-246.
HARVARD
Al-Dabbagh Hossein, M., Heidari, G., Askarian Abyaneh, H., K. Karegar, H. (2003). 'A Novel Fuzzy and Artificial Neural Network Representation of Overcurrent Relay Characteristics', International Journal of Engineering, 16(3), pp. 233-246.
VANCOUVER
Al-Dabbagh Hossein, M., Heidari, G., Askarian Abyaneh, H., K. Karegar, H. A Novel Fuzzy and Artificial Neural Network Representation of Overcurrent Relay Characteristics. International Journal of Engineering, 2003; 16(3): 233-246.
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