ISSN2320-2882
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Paper Title
"Advanced MPPT Techniques for Wind Power Generation Using PMSG: A Comparative Study of P&O and Genetic Algorithm Approaches"
Authors
Sairaj Muhaliya , Lavkesh Patidar
Keywords
Maximum Power Point Tracking (MPPT), Wind Energy Conversion System (WECS), Permanent Magnet Synchronous Generator (PMSG), Genetic Algorithm (GA), Perturb and Observe (P&O).
Abstract
In the context of renewable energy generation, efficient extraction of power from wind resources is of paramount importance. Maximum Power Point Tracking (MPPT) techniques play a crucial role in optimising the output of Wind Energy Conversion Systems (WECS), especially under fluctuating wind conditions. This study presents a comparative evaluation of two MPPT strategies--Perturb and Observe (P&O) and the Genetic Algorithm (GA)--implemented in a wind energy system equipped with a Permanent Magnet Synchronous Generator (PMSG). The PMSG has been chosen due to its high efficiency, robustness, and suitability for direct-drive configurations, eliminating the need for gearboxes.
The complete system is modelled and simulated using MATLAB/Simulink, considering a range of dynamic wind speed conditions. The performance of both MPPT techniques is analysed based on their ability to track the maximum power point efficiently. The simulation results indicate that while the conventional P&O method achieves a maximum output of 1049 kW and performs well under steady conditions, it exhibits limitations in terms of response time and output oscillations during wind fluctuations. In contrast, the GA-based MPPT algorithm showcases significantly improved performance, achieving a higher power output of 2785 kW, along with faster convergence and smoother power tracking.
The study highlights the potential of advanced, intelligent optimisation methods like Genetic Algorithms in enhancing the reliability and effectiveness of modern wind energy systems, particularly in real-world operating scenarios marked by dynamic environmental changes.
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IJCRT — journal style
""Advanced MPPT Techniques for Wind Power Generation Using PMSG: A Comparative Study of P&O and Genetic Algorithm Approaches"", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.13, Issue 10, page no.d503-d511, October 2025, Available :https://ijcrt.org/papers/IJCRT2510419.pdf
APA — 7th edition
Muhaliya, S., & Patidar, L. (2025). "Advanced MPPT Techniques for Wind Power Generation Using PMSG: A Comparative Study of P&O and Genetic Algorithm Approaches". International Journal of Creative Research Thoughts, 13(10), d503-d511. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510419
MLA — 9th edition
Muhaliya, Sairaj, and Lavkesh Patidar. ""Advanced MPPT Techniques for Wind Power Generation Using PMSG: A Comparative Study of P&O and Genetic Algorithm Approaches"." International Journal of Creative Research Thoughts, vol. 13, no. 10, 2025, pp. d503-d511, https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510419.
Chicago — 17th, bibliography
Muhaliya, Sairaj, and Lavkesh Patidar. ""Advanced MPPT Techniques for Wind Power Generation Using PMSG: A Comparative Study of P&O and Genetic Algorithm Approaches"." International Journal of Creative Research Thoughts 13, no. 10 (2025): d503-d511. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510419.
Harvard — author–date
Muhaliya, S. and Patidar, L. (2025) '"Advanced MPPT Techniques for Wind Power Generation Using PMSG: A Comparative Study of P&O and Genetic Algorithm Approaches"', International Journal of Creative Research Thoughts, 13(10), pp. d503-d511. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510419
IEEE — numbered reference
S. Muhaliya and L. Patidar, ""Advanced MPPT Techniques for Wind Power Generation Using PMSG: A Comparative Study of P&O and Genetic Algorithm Approaches"," IJCRT, vol. 13, no. 10, pp. d503-d511, Oct. 2025.
Vancouver — biomedical
Muhaliya S, Patidar L. "Advanced MPPT Techniques for Wind Power Generation Using PMSG: A Comparative Study of P&O and Genetic Algorithm Approaches". IJCRT. 2025 Oct;13(10):d503-d511.
AMA — 11th edition
Muhaliya S, Patidar L. "Advanced MPPT Techniques for Wind Power Generation Using PMSG: A Comparative Study of P&O and Genetic Algorithm Approaches". IJCRT. 2025;13(10):d503-d511. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510419
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2510419,
author = {Sairaj Muhaliya and Lavkesh Patidar},
title = {"Advanced MPPT Techniques for Wind Power Generation Using PMSG: A Comparative Study of P&O and Genetic Algorithm Approaches"},
journal = {International Journal of Creative Research Thoughts},
volume = {13},
number = {10},
pages = {d503-d511},
year = {2025},
month = {October},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510419}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Muhaliya, Sairaj
AU - Patidar, Lavkesh
TI - "Advanced MPPT Techniques for Wind Power Generation Using PMSG: A Comparative Study of P&O and Genetic Algorithm Approaches"
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 13
IS - 10
PY - 2025
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510419
SP - d503-d511
ER -
Issue
Volume 13 Issue 10,
October-2025
Pages : d503-d511
Article Information
- Published In
- International Journal of Creative Research Thoughts — Volume 13, Issue 10, October 2025
- Pages
- d503-d511
- Published
- October 2025
- Registration ID
- IJCRT_295274
- Published Paper ID
- IJCRT2510419
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- Indore, Madhya Pradesh, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 186
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510419
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT2510419.pdf
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