In recent times, there has been increasing interest in renewable power generation and electric vehicles within the domain of smart grids. The integration of electric vehicles with hybrid systems presents several critical challenges, including increased power loss, power quality issues, and voltage deviations. To tackle these challenges, researchers have proposed various techniques. Effective management of energy systems is essential for maximizing the benefits of integrating a hybrid system with a microgrid at an electric vehicle charging station. This research specifically aims to optimize the location and sizing of such a hybrid system within the microgrid. Additionally, an improved binary quantum-based Elk Herd optimizer approach is proposed. This approach addresses for optimally managing renewable energy sources and load uncertainty. The proposed system also considers the stochastic nature of electric vehicles and operational restrictions, encompassing diverse charging control modes. The proposed technique performance is implemented in MATLAB platform and compared against existing approaches. The analysis demonstrates the effectiveness in achieving optimal location and sizing for a hybrid system with an electric vehicle charging station. Additionally, the proposed approach contributes to minimizing power loss, electricity costs, and average waiting time. Furthermore, the proposed approach reduces computing time, net present cost, and emissions are 12.5 s, dollar, g year−1, respectively.
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November 2024
Research Article|
November 04 2024
Improved binary quantum-based Elk Herd optimizer for optimal location and sizing of hybrid system in micro grid with electric vehicle charging station
G. Muralikrishnan
;
G. Muralikrishnan
a)
(Conceptualization)
1
Associate Professor, Electrical and Electronics Engineering, S.A. Engineering College
, Chennai 600 077, Tamil Nadu, India
a)Author to whom correspondence should be addressed: murtkg14787@gmail.com
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K. Preetha;
K. Preetha
b)
(Supervision)
2
Assistant Professor, Electrical and Electronic Engineering, Erode Sengunthar Engineering College (Autonomous), Thudupathi, Perundurai 638057,
India
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S. Selvakumaran;
S. Selvakumaran
c)
(Supervision)
3
Research Scholar, Electrical and Electronic Engineering, Alagappa Chettiar Government College of Engineering and Technology
, Karaikudi 630 003, Tamil Nadu, India
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J. Nagendran
J. Nagendran
d)
(Supervision)
4
Assistant Professor, Electrical and Electronic Engineering, M.A.M. College of Engineering and Technology, Tiruchirappalli 621105, Tamil Nadu
, India
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a)Author to whom correspondence should be addressed: murtkg14787@gmail.com
b)
Electronic mail: preethakeee@gmail.com
c)
Electronic mail: sskariyalur46@gmail.com
d)
Electronic mail: nagenjay@gmail.com
J. Renewable Sustainable Energy 16, 064101 (2024)
Article history
Received:
May 22 2024
Accepted:
October 05 2024
Citation
G. Muralikrishnan, K. Preetha, S. Selvakumaran, J. Nagendran; Improved binary quantum-based Elk Herd optimizer for optimal location and sizing of hybrid system in micro grid with electric vehicle charging station. J. Renewable Sustainable Energy 1 November 2024; 16 (6): 064101. https://doi.org/10.1063/5.0220051
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