LAPSE:2023.24593
Published Article
LAPSE:2023.24593
Smart Grid Monitoring by Wireless Sensors Using Binary Logistic Regression
Hariprasath Manoharan, Yuvaraja Teekaraman, Irina Kirpichnikova, Ramya Kuppusamy, Srete Nikolovski, Hamid Reza Baghaee
March 28, 2023
This article focuses on addressing the data aggregation faults caused by the Phasor Measuring Unit (PMU) by installing Wireless Sensor Networks (WSN) in the grid. All data that is monitored by PMU should be sent to the base station for further action. But the data that is sent from PMU does not reach the main server properly in many situations. To avoid this situation, a sensor-based technology has been introduced in the proposed method for sensing the values that are monitored by PMU. Also, the basic parameters that are necessary for determining optimal solutions like energy consumption, distance and cost have been calculated for wireless sensors, whereas, for PMU optimal placements with cost analysis have been restrained. For analyzing and improving the accuracy of the proposed method, an effective Binary Logistic Regression (BLR) algorithm has been integrated with an objective function. The sensor will report all measured PMU values to an Online Monitoring System (OMS). To examine the effectiveness of the proposed method, the examined values are visualized in MATLAB and results prove that the proposed method using BLR is more effective than existing methods in terms of all parametric values and the much improved results have been obtained at a rate of 81.2%.
Keywords
binary logistic regression, phasor machine learning, Sensors, smart grids (intelligent networks), wireless network
Suggested Citation
Manoharan H, Teekaraman Y, Kirpichnikova I, Kuppusamy R, Nikolovski S, Baghaee HR. Smart Grid Monitoring by Wireless Sensors Using Binary Logistic Regression. (2023). LAPSE:2023.24593
Author Affiliations
Manoharan H: Department of Electronics and Communication Engineering, Audisankara College of Engineering and Technology, Gudur 524 101, India [ORCID]
Teekaraman Y: Faculty of Energy and Power Engineering, South Ural State University, Chelyabinsk 454 080, Russia
Kirpichnikova I: Faculty of Energy and Power Engineering, South Ural State University, Chelyabinsk 454 080, Russia
Kuppusamy R: Department of Electrical & Electronics Engineering, Sri Sairam College of Engineering, Bangalore 562106, India
Nikolovski S: Power Engineering Department, Faculty of Electrical Engineering, Computer Science and Information Technology, University of Osijek, 31000 Osijek, Croatia [ORCID]
Baghaee HR: Department of Electrical Engineering, Amirkabir University of Technology, Tehran 15875−4413, Iran [ORCID]
Journal Name
Energies
Volume
13
Issue
15
Article Number
E3974
Year
2020
Publication Date
2020-08-02
Published Version
ISSN
1996-1073
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PII: en13153974, Publication Type: Journal Article
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LAPSE:2023.24593
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doi:10.3390/en13153974
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Mar 28, 2023
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