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All Journal International Journal of Advances in Applied Sciences Bulletin of Electrical Engineering and Informatics
Bhukya Mangu
Osmania University
Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Power system contingency classification using machine learning technique Sandhya Rani Gongada; Muktevi Chakravarthy; Bhukya Mangu
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4031

Abstract

One of the most effective ways for estimating the impact and severity of line failures on the static security of the power system is contingency analysis. The contingency categorization approach uses the overall performance index to measure the system's severity (OPI). The newton raphson (NR) load flow technique is used to extract network variables in a contingency situation for each transmission line failure. Static security is categorised into five categories in this paper: secure (S), critically secure (CS), insecure (IS), highly insecure (HIS), and most insecure (MIS). The K closest neighbor machine learning strategy is presented to categorize these patterns. The proposed machine learning classifiers are trained on the IEEE 30 bus system before being evaluated on the IEEE 14, IEEE 57, and IEEE 118 bus systems. The suggested k-nearest neighbor (KNN) classifier increases the accuracy of power system security assessments categorization. A fuzzy logic approach was also investigated and implemented for the IEEE 14 bus test system to forecast the aforementioned five classifications.
A receiver-side power control method for series-series magnetic topology in inductive contactless electric vehicles battery charger application Bhukya Bhavsingh; Gotluru Suresh Babu; Bhukya Mangu; Ravikumar Bhukya
International Journal of Advances in Applied Sciences Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v12.i3.pp234-249

Abstract

Wireless power transfer (WPT) can be used to charge the battery conveniently and efficiently. In this paper, the investigation of high-efficiency S/S resonant magnetic topology in inductive wireless battery charging of electric vehicles (EVs) is analyzed, designed, and controlled. To regulate the output power efficiently rather than controlling the supply voltage, novel bidirectional switches are introduced to control the output power by using the duty cycle control method. The output power of the secondary side is derived and discussed based on the fundamental harmonic approximation (FHA) approach. A 1.5 kW, 120 mm distance, and 85 kHz resonance frequency are verified in MATLAB/Simulink.
Co-Authors Bhukya Bhavsingh Gotluru Suresh Babu Muktevi Chakravarthy Ravikumar Bhukya Sandhya Rani Gongada