Hybrid Maximum Power Point Tracking Method Based on Iterative Learning Control and Perturb & Observe Method

被引：48

作者：

Zhang, Xibeng ^{[1
]}

Gamage, Don ^{[1
]}

Wang, Benfei ^{[2
]}

Ukil, Abhisek ^{[1
]}

机构：

[1] Univ Auckland, Dept ECSE, Auckland 1010, New Zealand

[2] Sun Yat Sen Univ, Sch Intelligent Syst Engn, Guangzhou 510275, Peoples R China

来源：

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY | 2021年 / 12卷 / 01期

关键词：

Steady-state; Maximum power point trackers; Oscillators; Hybrid power systems; Iterative learning control; Hardware; Maximum power point tracking (MPPT); iterative learning control (ILC); hybrid energy storage system (HESS); solar photovoltaic; renewable energy; MPPT; ALGORITHM; SYSTEM; SIMULATION; DESIGN; SPEED;

D O I：

10.1109/TSTE.2020.3015255

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Maximum power point tracking (MPPT) is used to utilize intermittent solar power fully in the photovoltaic (PV) systems. Tracking the MPP fast, and accurately with changes in the solar irradiance, and the temperature is the goal of MPPT techniques. In this paper, a hybrid MPPT method based on iterative learning control (ILC), and perturb, and observe (P&O) algorithm is proposed. ILC can deal with the periodic variations to eliminate the steady-state oscillations, and errors, when the operation point is close to the MPP or a small irradiance variation occurs. In the proposed hybrid MPPT technique, a high frequency power P&O method without deadtime is used to improve the dynamic response when the irradiance changes rapidly. This paper presents the theoretical background of the hybrid MPPT algorithm, design, and stability analysis. Simulation, and hardware validation results substantiate the effectiveness of the proposed method.

引用

页码：659 / 670

页数：12

共 37 条

[1] An Accurate Method for MPPT to Detect the Partial Shading Occurrence in a PV System [J].

Ahmed, Jubaer ;

Salam, Zainal .

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 13 (05) :2151-2161

[2] A Modified P&O Maximum Power Point Tracking Method With Reduced Steady-State Oscillation and Improved Tracking Efficiency [J].

Ahmed, Jubaer ;

Salam, Zainal .

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2016, 7 (04) :1506-1515

[3] Efficiency Optimization of a DSP-Based Standalone PV System Using Fuzzy Logic and Dual-MPPT Control [J].

Al Nabulsi, Ahmad ;

Dhaouadi, Rached .

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2012, 8 (03) :573-584

[4] A novel maximum power point tracking technique based on fuzzy logic for photovoltaic systems [J].

Al-Majidi, Sadeq D. ;

Abbod, Maysam F. ;

A-Raweshidy, Hamed S. .

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2018, 43 (31) :14158-14171

[5] Conventional and modified MPPT techniques with direct control and dual scaled adaptive step-size [J].

Amir, Aamir ;

Amir, Asim ;

Selvaraj, Jeyraj ;

Rahim, Nasrudin A. ;

Abusorrah, Abdullah M. .

SOLAR ENERGY, 2017, 157 :1017-1031

[6]

[Anonymous], 2019, WELCOME CLIMATE DATA

[7] BETTERING OPERATION OF ROBOTS BY LEARNING [J].

ARIMOTO, S ;

KAWAMURA, S ;

MIYAZAKI, F .

JOURNAL OF ROBOTIC SYSTEMS, 1984, 1 (02) :123-140

[8] Hybrid maximum power point tracking algorithm with improved dynamic performance [J].

Bahrami, Milad ;

Gavagsaz-Ghoachani, Roghayeh ;

Zandi, Majid ;

Phattanasak, Matheepot ;

Maranzanaa, Gael ;

Nahid-Mobarakeh, Babak ;

Pierfederici, Serge ;

Meibody-Tabar, Farid .

RENEWABLE ENERGY, 2019, 130 :982-991

[9] Power Reserves Control for PV Systems With Real-Time MPP Estimation via Curve Fitting [J].

Batzelis, Efstratios I. ;

Kampitsis, Georgios E. ;

Papathanassiou, Stavros A. .

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2017, 8 (03) :1269-1280

[10]

Bien Z., 2010, ITERATIVE LEARNING C

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