English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The most common fault in the distribution network is the single line to ground fault (SLGF). With earthling in the distribution network, it causes electrical arc as well as a high voltage in the faulted phase compared to other two healthy phases. It increases the danger of separation and isolation in the power network. One of the classical technique to control the arc is through Peterson Coil (PC), which detects and turns off/reduces the electrical arc making the network safer, increasing its reliability and device's safety. To control the PC, some of the techniques used in this research area are PID, FL, NN etc. This paper presents Adaptive Neural-Fuzzy Inference System (ANFIS) technique to controlling the PC. It gives the best results by detecting the fault, reducing the electrical arc and minimizing the fault current to the rated current in a very short time. Moreover, this research focuses on suppressing fault current by looking at its higher and lower peaks. Also, it calculates the opposing inductance to compensate the capacitance caused. It will save thousands of tons of copper costs. This research was conducted using MATLAB. For the validity of the proposed technique results, PID control technique was used.

Optimization of detection of single line to ground fault by controlling peterson coil through ANFIS