Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)

Performance of Fuel Cell and PV Integrated Hybrid DC/AC Microgrid Based on the Grey Wolf Optimization Algorithm

Authors
Pradeep Mogilicharla1, *, B. Sirisha1
1Electrical Engineering Dept., University College of Engineering(A), Osmania University, Hyderabad, India
*Corresponding author. Email: pradeep.mrtgpower@gmail.com
Corresponding Author
Pradeep Mogilicharla
Available Online 9 November 2023.
DOI
10.2991/978-94-6463-252-1_75How to use a DOI?
Keywords
grey wolf optimization; MPPT; PEM fuel cells; PV systems; direct-quadrature (dq) Axis control approach; synchronous reference frame theory
Abstract

This paper presents performance of enhanced hybrid DC/AC microgrid system. Maximum active power possible to the utility grid can be delivered with renewable energy sources like PEMFC (proton exchange membrane fuel cells) and PV (photovoltaic systems). Mathematical modelling is used to characterize the MG system, which consists of a photovoltaic system, a PEMFC, and a power source inverter. In order to boost performance and improve PV module efficiency, GWO (grey wolf optimization) based on MPPT (maximum power point tracking) is proposed. A Digital PI controller is proposed to control the circuit in order to increase the PEMFC's efficiency. The direct-quadrature (dq) Axis control approach based on SRFT(synchronous reference frame theory) is used to control the suggested inverter. The performance of the MG system is evaluated under different loading and weather conditions. Based on the characteristics of fuel cells and solar panels, the results of MATLAB simulation demonstrate that the optimized MG system can generate and use active Power. The DC-bus voltage stabilization is accordingly better on the hybrid DC/AC Micro-Grid. Moreover, the MG's power output is enhanced via GWO tuning based on MPPT. It also produces respectable results to use GWO, which has a greater efficiency of 98.9% and an output current total harmonic distortion of 2.21%.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)
Series
Advances in Engineering Research
Publication Date
9 November 2023
ISBN
10.2991/978-94-6463-252-1_75
ISSN
2352-5401
DOI
10.2991/978-94-6463-252-1_75How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Pradeep Mogilicharla
AU  - B. Sirisha
PY  - 2023
DA  - 2023/11/09
TI  - Performance of Fuel Cell and PV Integrated Hybrid DC/AC Microgrid Based on the Grey Wolf Optimization Algorithm
BT  - Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)
PB  - Atlantis Press
SP  - 751
EP  - 760
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-252-1_75
DO  - 10.2991/978-94-6463-252-1_75
ID  - Mogilicharla2023
ER  -