A Communication Model Framework for Electric Transmission Line Monitoring Using Artificial Bee Colony Algorithm

Author:

Jeyanthi C.1,Sait H. Habeebullah2,Chandrasekaran K.3,Columbus C. Christopher1

Affiliation:

1. PSN College of Engineering and Technology, Tirunelveli, Tamil Nadu 627152, India

2. Anna University Regional Centre, BIT Campus, Tiruchirapalli, Tamil Nadu 620024, India

3. National Institute of Technology, Karaikal, Puducherry 609609, India

Abstract

The natural calamity and physical malfunction in the overhead transmission line cause bad impact on the networks such as mechanical failures, power losses, reduction of line capacity, and voltage drop. These adverse impacts can be reduced by implementing proper monitoring systems. Wireless sensor network is an apt mechanism to monitor the overhead transmission network because of its physical configuration. This paper portrays the communication between wireless sensor networks and central data processing station. Cellular communication can directly transmit information through an assisted cellular module (CM) based on the probability of cellular coverage. In this paper, one of the modern optimization techniques, i.e., artificial bee colony algorithm, is used to study the problem of CM placement of cellular communication. By using this algorithm, the optimal number and location of the CMs for a test system varied from 10 to 100 are determined. A novel optimal link path scheme is proposed to check the condition of the required quality of services of both cellular/ZigBee users. The attained results show that the methodology is best suited to acquire low cost solution for the cellular module placement problem.

Publisher

World Scientific Pub Co Pte Lt

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Electrical and Electronic Engineering,Hardware and Architecture

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Monitoring Technology of Abnormal Displacement of BeiDou Power Line Based on Artificial Neural Network;Computational Intelligence and Neuroscience;2022-08-31

2. Dynamic Identification Method of Transmission Line Defects Based On Moving Edge Calculation;2021 8th International Forum on Electrical Engineering and Automation (IFEEA);2021-09

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