Digital overcurrent relay with conventional curve modeling using Levenberg-Marquardt backpropagation

Overcurrent relays (OCRs) play an important role in the protection component that requires high reliability to maintain high security for power systems. Modeling of the OCRcurve using methods like the direct data storage and curve fitting gave only approximate models. Therefore, in this paper proposes modeling of OCRs using Levenberg-Marquardt backpropagation (LMBP). An implementation of OCR in the digital OCR used ARM microcontroller STM32F407VGT6 is to improve performance of the relay significantly. LMBP is developed using different numbers of neurons. The current and opening time of the circuit breaker are used as input and output in the LMBP training. LMBP developed in the OCR curve model using sample data from protection coordination is implemented as real time in Hess Indonesia Corporation. The weights obtained by the LMBP are used to run the LMBP program in the digital OCR. The well known digital OCR product is used for comparison. The results show that this proposed method is accurate and encouraging with percentage error is 0.24% and very promising to be applied in the digital OCR.