Issue |
E3S Web Conf.
Volume 601, 2025
The 3rd International Conference on Energy and Green Computing (ICEGC’2024)
|
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Article Number | 00064 | |
Number of page(s) | 19 | |
DOI | https://doi.org/10.1051/e3sconf/202560100064 | |
Published online | 16 January 2025 |
Performance Enhancement of a Solar Photovoltaic System with Differential Evolution-Optimized Quasi Sliding Mode Control
1 MIN Research Group, LASMAR Laboratory, Higher School of Technology Meknes, Moulay Ismail University of Meknes, Morocco
2 REIPT Laboratory, Faculty of Sciences and Technology, B.P. 509, Boutalamine, Errachidia, Moulay Ismail University of Meknes, Morocco
3 LASMAR Laboratory, Faculty of Sciences Meknes, Moulay Ismail University of Meknes, Morocco
* Corresponding author: h.rizki@edu.umi.ac.ma
This paper presents a novel approach to enhancing the performance of a solar photovoltaic (PV) system by integrating a Differential Evolution (DE) optimization algorithm into the design of a Quasi Sliding Mode Controller (QSMC). The proposed method aims to address the challenges associated with Conventional Sliding Mode Control (CSMC), such as chattering and suboptimal tracking accuracy, which can significantly impact the stability and efficiency of PV systems. Simulation results show that the DE-optimized QSMC reduces tracking error to 0.05 V, while conventional SMC results in a tracking error of 0.15 V. Chattering amplitude is also significantly reduced, from 0.12 A to 0.03 A and the response time is improved from 0.8 seconds to 0.5 seconds. By leveraging the robustness of QSMC and the flexibility of DE, the DE-QSMC is fine-tuned to minimize tracking errors, reduce chattering, and maintain optimal performance under varying environmental conditions. The stability of the proposed technique is rigorously analyzed using the Lyapunov function theorem, ensuring robust system behavior. The effectiveness of the DE-optimized QSMC is validated through simulations conducted on the Matlab platform, demonstrating superior performance compared to conventional control techniques.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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