Adaptive control-based Isolated bi-directional converter for G2V& V2G charging with integration of the renewable energy source

Srinivas Singirikonda; Yeddula Pedda Obulesu; Ramani Kannan; K. Jyotheeswara Reddy; G. Kiran Kumar; Wajdi Alhakami; Abdullah Baz; Hosam Alhakami

Energy Reports (Nov 2022)

Adaptive control-based Isolated bi-directional converter for G2V& V2G charging with integration of the renewable energy source

Srinivas Singirikonda,
Yeddula Pedda Obulesu,
Ramani Kannan,
K. Jyotheeswara Reddy,
G. Kiran Kumar,
Wajdi Alhakami,
Abdullah Baz,
Hosam Alhakami

Affiliations

Srinivas Singirikonda: School of Electrical Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India; Corresponding authors.
Yeddula Pedda Obulesu: School of Electrical Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India; Corresponding authors.
Ramani Kannan: Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, Malaysia; Corresponding authors.
K. Jyotheeswara Reddy: School of Electrical and Electronics Engineering, REVA University, Bangalore, India
G. Kiran Kumar: School of Electrical Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India
Wajdi Alhakami: Department of Information Technology, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
Abdullah Baz: Department of Computer Engineering, College of Computer and Information Systems, Umm Al-Qura University, Makkah, Saudi Arabia
Hosam Alhakami: Department of Computer Science, College of Computer and Information Systems, Umm Al-Qura University, Makkah, Saudi Arabia

Journal volume & issue: Vol. 8
pp. 11416 – 11428

Abstract

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In this research paper, Adaptive control-based Isolated bi-directional converter for modernized electric vehicle system is introduced with control on charge and discharge of the electric vehicle (EV) battery as per the reference value. The EV battery is operated in two modes, such as charge (Grid-to-Vehicle) mode and discharge (vehicle-to-grid) mode. In charging mode, constant current and constant voltage (CCCV) control is adopted with control on charging voltage and current. Whereas in discharging mode, constant current (CC) control is adopted for control on discharge current from battery into the grid. The grid is also interconnected to PV system for renewable energy power sharing. In both the control techniques, ANFIS is integrated for better performance of the battery during charge and discharge conditions. The ANFIS takes input from error generated by comparison of reference and measured value and produces the required duty ratio value. The training of the fuzzy structure is done using data generated from the PI controller input and output. The training uses hybrid algorithm for adapting the data points considered from the PI controller. The EV battery is charged using the conventional AC grid and the renewable energy source in G2V mode, and the EV battery and renewable energy sources are used to supply power to the AC load in the V2G mode, which reducing the load demand on the AC grid. The DC-Link voltage and power to the AC load are kept constant in both modes of operation by using a synchronous reference frame controlled VSC and an ANFIS controlled dual active full bridge converter. The incremental conductance MPPT algorithm is used to control the Photo Voltaic Array (PVA). The proposed work is implemented using MATLAB/Simulink and HIL performance of the proposal system is examined in the RT-LAB OP-5700 real time simulator environment.

Published in Energy Reports

ISSN: 2352-4847 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: http://www.journals.elsevier.com/energy-reports/

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