Adaptive sliding mode control based on maximum power point tracking for boost converter of photovoltaic system under reference voltage optimizer

被引：0
作者：
Torchani, Borhen [1 ]
Azar, Ahmad Taher [2 ,3 ,4 ]
Sellami, Anis [1 ]
Ahmed, Saim [2 ,3 ]
Hameed, Ibrahim A. [5 ]
Kasim Ibraheem, Ibraheem [6 ]
Al-Obaidi, Moamin Ibrahim Jameel [7 ]
机构：
[1] LISIER Laboratory, ENSIT, University of Tunis, Tunis
[2] College of Computer and Information Sciences, Prince Sultan University, Riyadh
[3] Automated Systems and Soft Computing Lab (ASSCL), Prince Sultan University, Riyadh
[4] Faculty of Computers and Artificial Intelligence, Benha University, Benha
[5] Department of ICT and Natural Sciences, Norwegian University of Science and Technology, Alesund
[6] Department of Electrical Engineering, College of Engineering, University of Baghdad, Baghdad
[7] Department of Communication Technical Engineering, Uruk University, Baghdad
来源：
Frontiers in Energy Research | 2024年 / 12卷
关键词：
adaptive sliding mode control; boost converter; maximum power point tracking; photovoltaic system; reference voltage optimizer;
D O I：
10.3389/fenrg.2024.1485470
中图分类号：
学科分类号：
摘要：
This article presents an innovative APISMC method applied to PVS, integrating the MPPT technique for a boost converter. The primary objective of this approach is to maximize the converter’s output power while ensuring optimal operation in the face of varying environmental conditions such as solar irradiance and temperature, while dynamically adapting to variations in system parameters, as demonstrated by the obtained results. To achieve this, a RVO is employed to generate reference voltage and power. A PI controller calculates the reference current based on this power. The APISMC control modeling utilizes all its reference variables to synthesize the sliding surface and duty cycle for optimal boost converter control. Simulations conducted demonstrate superior performance in terms of stability, speed, and control of the converter compared to traditional MPPT algorithms. The main contributions of this article include an improvement in system robustness against irradiance variations, thanks to the integration of an adaptive algorithm and a PI controller within the SMC. Moreover, the proposed theoretical and practical framework enables rapid MPPT attainment by adjusting the duty cycle in real-time, optimizing maximum power extraction and ensuring stable regulation even under non-ideal conditions. Copyright © 2024 Torchani, Azar, Sellami, Ahmed, Hameed, Kasim Ibraheem and Al-Obaidi.
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