Performance Improvement in SEPIC Converter Using Modified Seagull Optimization Techniques

International Journal of Electrical and Electronics Engineering
© 2024 by SSRG - IJEEE Journal
Volume 11 Issue 8
Year of Publication : 2024
Authors : Manjushree Kumari Jayaraman, Nagarajan Ramalingam
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How to Cite?

Manjushree Kumari Jayaraman, Nagarajan Ramalingam, "Performance Improvement in SEPIC Converter Using Modified Seagull Optimization Techniques," SSRG International Journal of Electrical and Electronics Engineering, vol. 11,  no. 8, pp. 50-58, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I8P105

Abstract:

This research provides a novel technique for enhancing the performance of a Single-Ended Primary Inductor Converter (SEPIC) by utilizing Modified Seagull Optimization Algorithm (MSOA) techniques. The SEPIC converter is widely employed in power electronics for its versatility in voltage regulation. However, challenges related to efficiency and optimization persist. To solve these problems, a modified version of the Seagull Optimization Algorithm is presented in this work. The proposed technique is employed to optimize the control parameters of the SEPIC converter, aiming to achieve improved efficiency and reduced losses. The results of the simulation show how well the Modified Seagull Optimization Algorithm performs the converter under different operating situations. The findings suggest that the proposed method holds promise for practical applications in power electronics, contributing to the advancement of energy-efficient converter designs. Based on a new methodology, the ideal sampling period was identified for the controller to achieve optimal performance. The main research tool is a software suite called MATLAB/Simulink. The main results show that the modified SOA and its intended parameters best meet the requirements of the MPPT controller for PV systems.

Keywords:

SEPIC converter, Modified Seagull Optimization, Single-ended primary inductor converter, Energy-efficient design, Converter optimization.

References:

[1] Ray Ridley, “Analyzing the SEPIC Converter,” Power Systems Design Europe, pp. 14-18, 2006.
[Google Scholar] [Publisher Link]
[2] Roberto F. Coelho, Filipe M. Concer, and Denizar C. Martins, “Analytical and Experimental Analysis of DC-DC Converters in Photovoltaic Maximum Power Point Tracking Applications,” IECON 2010-36th Annual Conference on IEEE Industrial Electronics Society, Glendale, AZ, USA, pp. 2778-2783, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Nur Mohammad et al., “Parasitic Effects on the Performance of DC-DC SEPIC in Photovoltaic Maximum Power Point Tracking Applications,” Smart Grid and Renewable Energy, vol. 4, no. 1, pp. 113-121, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Roberto Francisco Coelho, and Denizar Cruz Martins, “An Optimized Maximum Power Point Tracking Method Based on PV Surface Temperature Measurement,” Sustainable Energy-Recent Studies, pp. 89-114, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[5] S. J. Chiang, Hsin-Jang Shieh, and Ming-Chieh Chen, “Modeling and Control of PV Charger System with SEPIC Converter,” IEEE Transactions on Industrial Electronics, vol. 56, no. 11, pp. 4344-4353, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Muhammad H. Rashid, Power Electronics-Circuits, Devices, and Applications, Upper Saddle River, NJ, Pearson Prentice Hall, 2004.
[Google Scholar]
[7] Anjanee Kumar Mishra, and Bhim Singh, “High Gain Single Ended Primary Inductor Converter with Ripple Free Input Current for Solar Powered Water Pumping System Utilizing Cost-Effective Maximum Power Point Tracking Technique,” IEEE Transactions on Industry Applications, vol. 55, no. 6, pp. 6332-6343, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Hamza Mohammed Ridha Al-Khafaji, “Improving Quality Indicators of the Cloud-Based IoT Networks Using an Improved Form of Seagull Optimization Algorithm,” Future Internet, vol. 14, no. 10, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Rajan Kumar, and Bhim Singh, “Solar PV Array Fed Water Pumping System Using SEPIC Converter-Based BLDC Motor Drive,” 2014 Eighteenth National Power Systems Conference (NPSC), Guwahati, India, pp. 1-5, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Gaurav Dhiman, and Vijay Kumar, “Seagull Optimization Algorithm: Theory and Its Applications for Large-Scale Industrial Engineering Problems,” Knowledge-Based Systems, vol. 165, pp. 169-196, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Ahmad Elkhateb et al., “Fuzzy-Logic-Controller-Based SEPIC Converter for Maximum Power Point Tracking,” IEEE Transactions on Industry Applications, vol. 50, no. 4, pp. 2349-2358, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Anjanee Kumar Mishra, and Bhim Singh, “High Gain Single-Ended Primary Inductor Converter with Ripple Free Input Current for Solar Powered Water Pumping System Utilizing Cost-Effective Maximum Power Point Tracking Technique,” IEEE Transactions on Industry Applications, vol. 55, no. 6, pp. 6332-6343, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[13] J. S. R. Jang, C.T. Sun, and E. Mizutani, “Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence [Book Review],” IEEE Transactions on Automatic Control, vol. 42, no. 10, pp. 1482-1484, 1997.
[CrossRef] [Google Scholar] [Publisher Link]
[14] L.A. Zadeh, “Soft Computing and Fuzzy Logic,” IEEE Software, vol. 11, no. 6, pp. 48-56, 1994.
[CrossRef] [Google Scholar] [Publisher Link]
[15] S. Mitra, and Y. Hayashi, “Neuro-Fuzzy Rule Generation: Survey in Soft Computing Framework,” IEEE Transactions on Neural Networks, vol. 11, no. 3, pp. 748-768, 2000.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Sergio Jurado et al., “Hybrid Methodologies for Electricity Load Forecasting: Entropy-Based Feature Selection with Machine Learning and Soft Computing Techniques,” Energy, vol. 86, pp. 276-291, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Quanmin Zhu, and Ahmad Taher Azar, “Complex System Modelling and Control through Intelligent Soft Computations, 1st ed., Springer Cham, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Ruonan Liu et al., “Artificial Intelligence for Fault Diagnosis of Rotating Machinery: A Review,” Mechanical Systems and Signal Processing, vol. 108, pp. 33-47, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Iman Moeini et al., “Modeling the Time-Dependent Characteristics of Perovskite Solar Cells,” Solar Energy, vol. 170, pp. 969-973, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Amir Mosavi, Alvaro Lopez, and Annamária R. Varkonyi-Koczy, “Industrial Applications of Big Data: State of the Art Survey,” Recent Advances in Technology Research and Education,” pp. 225-232, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Abteen Ijadi Maghsoodi et al., “Renewable Energy Technology Selection Problem Using Integrated H-Swara-Multimoora Approach,” Sustainability, vol. 10, no. 12, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Harvinder Singh et al., “Metaheuristics for Scheduling of Heterogeneous Tasks in Cloud Computing Environments: Analysis, Performance Evaluation, and Future Directions,” Simulation Modelling Practice and Theory, vol. 111, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Jafar Meshkati, and Faramarz Safi-Esfahani, “Energy-Aware Resource Utilization Based on Particle Swarm Optimization and Artificial Bee Colony Algorithms in Cloud Computing,” The Journal of Supercomputing, vol. 75, no. 5, pp. 2455-2496, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[24] M.S. Sanaj, and P.M. Joe Prathap, “An Efficient Approach to the Map-Reduce Framework and Genetic Algorithm-Based Whale Optimization Algorithm for Task Scheduling in the Cloud Computing Environment,” Materials Today: Proceedings, vol. 37, pp. 3199-3208, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Dabiah Alboaneen et al., “A Metaheuristic Method for Joint Task Scheduling and Virtual Machine Placement in Cloud Data Centers,” Future Generation Computer Systems, vol. 115, pp. 201-212, 2021.
[CrossRef] [Google Scholar] [Publisher Link]