Overcurrent relay curve modeling and its application in the real industrial power systems using adaptive neuro fuzzy inference system

Create an accurate model with over-current relays (OCRs) play an important role in the coordination of power system protection. Modeling of the OCR using methods like the direct data storage and software models gave only approximate models. Moreover, modeling based on mathematical models is not appropriate to deal with ill-defined and uncertain systems. Therefore, in this paper proposes modeling of OCRs using adaptive neuro fuzzy inference system (ANFIS). ANFIS is developed using different numbers and types of membership functions (MFs). Each MF is implemented using training and checking data.

The load current and time of opening of the circuit breaker are used as input and output in the ANFIS training. ANFIS, which is developed in the OCR curve model using sample data from protection coordination, is implemented in Hess Indonesia Corporation. Different types of MFs are to obtain the optimal design of OCR curves. The result of ANFIS in the OCR curve modeling is accurate and encouraging; thus, the ANFIS model can be used in digital relays and applied successfully in the real systems. In all cases, ANFIS models using 30 Gbell-type MFs yields a very minimum average percentage error of 0.028419 %.

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