International Journal of Intelligence Science

Volume 11, Issue 1 (January 2021)

ISSN Print: 2163-0283   ISSN Online: 2163-0356

Google-based Impact Factor: 0.58  Citations  

Fuzzy Based Algorithm for Stage-I of Cascaded Intelligent Relaying

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DOI: 10.4236/ijis.2021.111003    380 Downloads   1,081 Views  

ABSTRACT

In the present scenario the protection system has become an important issue in the field of the power system. An Intelligent protection system has been introduced in many sectors like low voltage DC breakers, VCB, SF6 and so on. The said protection schemes have been developed to control the moving contacts using intelligent algorithms for tripping overall load against phase to ground faults occurring within the system. The related works have introduced Trapezoidal and Triangular membership functions as input to the fuzzy inference system. It is also found that the Fuzzy Logic Controller has been designed by taking two inputs as current and voltage. The output membership function has been preferred by implementing Trapezoidal and Gaussian membership functions. In this paper, a new concept based over current protection scheme has been introduced. Intelligent relaying technique has been used to trip a particular load against over current fault by introducing multistage cascaded intelligent relaying. Initially, the proposed method is carried out for Stage-I and reported by incorporating fuzzy algorithm by taking current error and current error rates as input using Gaussian membership function to the black box and fed signal to the breaker as output using trapezoidal and triangular membership function respectively to control the loads connected in the system. The best-fit membership function as input to the fuzzy engine is shown here is Gaussian membership function. The analysis reported here by taking both the fault scenario as phase to phase and phase to ground respectively.

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Samonto, S. , Kar, S. , Pal, S. , Sekh, A. and Sarkar, B. (2021) Fuzzy Based Algorithm for Stage-I of Cascaded Intelligent Relaying. International Journal of Intelligence Science, 11, 31-43. doi: 10.4236/ijis.2021.111003.

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