Fault Detection in Power Distribution

Abstract

Background : In present scenario electricity theft is a major problem for government. This problem affects Indian economy since GDP goes down due to theft. Electricity is a part of living and its theft effects the common man because indirectly common man has to pay for the theft done by someone else in form of extra charges. Methods: In this paper, we present a novel identification pattern-based energy fault detector, by leveraging the customers' normal and faulty line. The target of this paper is to implement a system to monitor the readings and to find the fault in power line in real time. Manipulations in readings of meter are impossible. Results: There is a real time monitoring of meters. Readings could be provided to customers on daily, weekly, monthly or yearly basis. As soon as there occur a fault, it could be rectified because detection is on real time basis and further message can be sent to customer about the fault. Conclusion: A comparison of developed real time monitoring system is done with GSM meters and analog meters.

Taylor political optimizer‐based cluster head selection in IOT‐assisted WSN networks

“…For 10 rounds, the energy evaluated by MEQSA‐OLSRv2 is 9.200 J, EOMR is 9.092 J, EMEER is 9.160 J, FGGWO is 9.122 J, TSGWO is 9.234 J, and developed Taylor‐PO is 9.269 J. Also, for 100 rounds, the energy evaluated by MEQSA‐OLSRv2 is 1.080 J, EOMR is 0.399 J, EMEER is 0.434 J, FGGWO is 0.437 J, TSGWO is 1.719 J, and developed Taylor‐PO is 2.126 J 33‐35 …”

“…Also, for 100 rounds, the energy evaluated by MEQSA-OLSRv2 is 1.080 J, EOMR is 0.399 J, EMEER is 0.434 J, FGGWO is 0.437 J, TSGWO is 1.719 J, and developed Taylor-PO is 2.126 J. [33][34][35] The assessment of techniques using throughput is depicted in Figure 7c). For 10 rounds, the throughput evaluated by MEQSA-OLSRv2 is 170.…”