Enhancing photovoltaic MPPT with P&O algorithm performance based on adaptive PID control using exponential forgetting recursive least squares method

被引:4
作者
Girgis, Meena E. [1 ]
Elkhateeb, Nasr A. [2 ]
机构
[1] Cairo Univ, Dept Elect & Elect Commun Engn, Giza, Egypt
[2] Modern Acad Engn & Technol, Cairo, Egypt
关键词
Photovoltaic; MPPT; Adaptive; Recursive-least-squares; PID-control; P&O algorithm; STAND-ALONE; MODEL; IMPLEMENTATION; DESIGN;
D O I
10.1016/j.renene.2024.121801
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
To maximize power transfer from the PV panel, a Perturb and Observe (P&O) algorithm and a feedback controller are used to create the Maximum Power Point Tracking (MPPT) algorithm. The dynamic performance of the MPPT algorithm depends on the feedback controller's ability to track the PV panel voltage to the reference voltage from the P&O algorithm. This research introduces an adaptive Proportional-Integral- Derivative (PID) controller that improves the dynamic characteristics of the MPPT algorithm. The proposed adaptive control technique utilizes a PID controller and the exponential forgetting recursive least squares (EFRLS) algorithm to update the PID gains online. The verification process involves simulations under three scenarios: slow and fast variations in temperature, solar insolation, resistive load, and partial shading situations. The proposed adaptive PID controller performs robustly during tracking PV panel voltage under different atmospheric conditions.
引用
收藏
页数:12
相关论文
共 38 条
[1]  
Astrom K.J., 2006, Advanced PID control
[2]   An improved method based on fuzzy logic with beta parameter for PV MPPT system [J].
Bisht, Rahul ;
Sikander, Afzal .
OPTIK, 2022, 259
[3]   Improvement and validation of a model for photovoltaic array performance [J].
De Soto, W ;
Klein, SA ;
Beckman, WA .
SOLAR ENERGY, 2006, 80 (01) :78-88
[4]   Assessment of Perturb and Observe MPPT Algorithm Implementation Techniques for PV Pumping Applications [J].
Elgendy, Mohammed A. ;
Zahawi, Bashar ;
Atkinson, David J. .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2012, 3 (01) :21-33
[5]   Dynamic inertia weight artificial bee colony versus GA and PSO for optimal tuning of PID controller [J].
Elkhateeb, Nasr A. ;
Badr, R. I. .
INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL, 2014, 22 (04) :307-317
[6]   Performance improvement of hybrid renewable energy sources connected to the grid using artificial neural network and sliding mode control [J].
Elnozahy, Ahmed ;
Yousef, Ali M. ;
Abo-Elyousr, Farag K. ;
Mohamed, Moayed ;
Abdelwahab, Saad A. Mohamed .
JOURNAL OF POWER ELECTRONICS, 2021, 21 (08) :1166-1179
[7]   Comparison of photovoltaic array maximum power point tracking techniques [J].
Esram, Trishan ;
Chapman, Patrick L. .
IEEE TRANSACTIONS ON ENERGY CONVERSION, 2007, 22 (02) :439-449
[8]   Multivariable Online Adaptive PID Controller for Plasma Current, Shape, and Position in Tokamaks [J].
Fahmy, Rania A. ;
Badr, Ragia I. ;
Rahman, Farouk A. .
JOURNAL OF FUSION ENERGY, 2016, 35 (06) :831-840
[9]   Advanced Variable Step Size Incremental Conductance MPPT for a Standalone PV System Utilizing a GA-Tuned PID Controller [J].
Feroz Mirza, Adeel ;
Mansoor, Majad ;
Ling, Qiang ;
Khan, Muhammad Imran ;
Aldossary, Omar M. .
ENERGIES, 2020, 13 (16)
[10]  
Guerrero M., 2015, Cuckoo Search via Lvy Flights and a Comparison with Genetic Algorithms, P91, DOI 10.1007978-3-319-10960-2_6