Artificial Neural Network with 3-Port Dc-Dc Converter Based Energy Management Scheme in Sustainable Energy Sources

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Evangelin Jeba J
C. R. Rajesh

Abstract

In micro grids, energy management is referred to as an information and control system that offers the essential functionality to ensure that the energy supply from the generation and distribution systems occurs at the lowest possible operational cost. Energy management systems (EMS) support distributed energy resource utilization in micro grids, especially when variable generation and pricing are present. In this paper, an Artificial Neural Network (ANN)-based energy management approach for a hybrid wind, solar and Battery Storage System (BSS) is presented. To sustain the DC voltage, a 3 Port DC-DC Converter is also proposed. While renewable energy systems have numerous advantages, one of the challenges they face is the intermittency of power generation, leading to fluctuations in the power supply to the grid. Therefore, EMS aims to reduce these variations. Another goal is to maintain the battery state of charge (SOC) within the allowed ranges to extend the battery life. The implementation is carried out in Simulink/Matlab platform. To demonstrate the efficacy of the suggested approach, we compare the Total Harmonic Distortion (THD) of the proposed controller (1.52%) with that of conventional controllers, including the ZSI-based PID controller (3.05%), PI controller (4.02%), and FO-PI (3.32%) controller.

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How to Cite
[1]
Evangelin Jeba J and C. R. Rajesh , Trans., “Artificial Neural Network with 3-Port Dc-Dc Converter Based Energy Management Scheme in Sustainable Energy Sources”, IJEAT, vol. 12, no. 6, pp. 22–29, Sep. 2023, doi: 10.35940/ijeat.F4249.0812623.
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Author Biographies

Evangelin Jeba J, Assistant Professor, Department of Electrical and Electronics Engineering, Maria College of Engineering and Technology, Attoor (Tamil Nadu), India

Evangelin Jeba J (Johnson) received her Bachelor of Engineering degree in Electrical and Electronics Engineering from Anna University, Chennai, India, in 2008 and her Master of Engineering degree in Power Systems Engineering from Anna University in Trinelveli, India, in 2011. She is currently pursuing the Ph.D. at SRM University in the area of Electric Vehicles. She has spent more than 13 years working as an Assistant Professor at the Department of Electrical and Electronics Engineering, starting in 2008. Her areas of research interst include EV, power systems, smart grid, micro grid and Renewable Energy Systems.

C. R. Rajesh, Assistant Professor, Department of Electrical and Electronics Engineering, CSI Institute of Technology, Thovalai (Tamil Nadu), India.

C.R. Rajesh (Chellaian Rosly Rajesh) received his Bachelor of Engineering degree in Electrical and Electronics Engineering from Kuvempu University, Karnataka, India, in 1998 and his Master of Engineering degree in Power Electronics and Drives from Sathyabama University, Chennai, India, in 2005. He has received his Ph.D degree in the Faculty of Electrical Engineering from Anna University, Chennai, India, in the year 2021. Since 1999 he has been working as an Assistant professor in the department of Electrical and Electronics Engineering, at the CSI Institute of Technology, Thovalai, India. His current research interest includes Multilevel Inverters, Shunt Active Filters, Power Electronics for Renewable Energy Systems, Facts Devices and EVs.

How to Cite

[1]
Evangelin Jeba J and C. R. Rajesh , Trans., “Artificial Neural Network with 3-Port Dc-Dc Converter Based Energy Management Scheme in Sustainable Energy Sources”, IJEAT, vol. 12, no. 6, pp. 22–29, Sep. 2023, doi: 10.35940/ijeat.F4249.0812623.
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