https://orcid.org/0000-0003-3773-4684
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Abstract
In this paper, a hybrid strategy is proposed for an innovative 15-level inverter method for the grid-connected photovoltaic (PV) system. The proposed technique is combined with the Zebra Optimization Algorithm (ZOA) plus the spiking neural network (SNN) and is called the ZOASNN method. The major goals of the ZOASNN approach are to fulfill the power demand of load, lessen harmonics, and improve the PV system power regulation or maximal energy conversion. The multilevel inverter (MLI) is used to operate at symmetrical and asymmetrical configurations aimed at utilizing reduced power components. The proposed ZOASNN controller develops the operating modes of two-generation methods to determine the converter switching states for this purpose. Using this control method, load demands are optimally fulfilled while external disturbances and fluctuations in system parameters are minimized. The proposed strategy is implemented in MATLAB and its performance is estimated with other algorithms, such as the Grasshopper Optimization Algorithm (GOA), the Random Forest Algorithm (RFA), and the Cuckoo Search Algorithm (CSA). The proposed method shows high efficiency, low total harmonics distortion (THD), and lower cost than other existing methods.
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No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
M. Anusuya
M Anusuya acquired bachelor’s degree in electrical and electronics engineering from Dhanalakshmi Srinivasan Engineering College, Perambalur, Tamilnadu, India in 2006. She obtained masters degree in power electronic and drives in 2012 and now pursuing doctoral degree in electrical engineering from Annamalai University, Tamil Nadu. Her areas of interest include power electronics, embedded system, modeling, VLSI design and solid state drives. Her career spans 13 years of teaching experience and is currently working as a research scholar in the Department of Electrical Engineering at Annamalai University, Annamalai Nagar, Chidambaram, Tamil Nadu, India. Corresponding author. Email: [email protected]
R. Geetha
R Geetha obtained her bachelor’s in electrical and electronics engineering from the University of Madras in 2001. She continued to receive her master’s in power systems engineering in 2008 and completed doctoral in electrical engineering from the Annamalai University in 2017. Her areas of interest include power electronics, solid state drives, HVDC transmission, intelligent control techniques and embedded systems. Her career spans 17 years of teaching experience and she is currently an associate professor in the Department of Electrical Engineering at the Annamalai University. She published papers in more than 11 international journals. Email: [email protected]
R. Ilango
R Ilango received BE degree in EEE from Regional Engineering College (REC) presently (National Institute of Technology (NIT) affiliated to Bharathidasan University, Trichy, Tamil Nadu, India in 1996, MTech degree in high voltage engineering from SASTRA University Thanjour, Tamil Nadu, India in 2002 and PhD degree in power systems engineering from Anna University, Chennai, Tamil Nadu, India in 2016. Presently, he is working as professor in Department of Electrical and Electronics Engineering K.Ramakrishnan College of Engineering, Trichy, Tamil Nadu, India. He has 21 years of teaching experience and published papers in national and international journals. His research interests include electrical vehicles, Flexible A C Transmission System, high voltage engineering, power system protection and power quality analysis. He is a life Member of Indian Society for Technical Education (ISTE) and Member of Institution of Engineers (MIE). Email: [email protected]