Maximum power point tracking for photovoltaic systems under partial shading conditions via modified model predictive control

被引:0
|
作者
Loghman Samani
Rahmatollah Mirzaei
机构
[1] The University of Kurdistan,Department of Electrical Engineering
来源
Electrical Engineering | 2021年 / 103卷
关键词
Maximum power point tracking; Model predictive control; Cuk converter; Photovoltaic systems;
D O I
暂无
中图分类号
学科分类号
摘要
In recent years different solutions for MPPT have been proposed in many papers. MPC method is considered as it is straightforward in both method and implementation. MPC method has a faster dynamic and better steady-state response. But, the dynamic and steady-state response depends on step size in the production of the reference current in MPC method. In this article, a MMPC method was used for a Cuk converter to achieve MPPT in photovoltaic systems. In the proposed method under uniform conditions, the PI controller applied to the error between the initial reference current from P&O and the actual current of the photovoltaic array. The reference current from the PI controller and the predictive current are applied to the cost function and the required switching pulses are generated. A two-stage algorithm was proposed under non-uniform conditions. IN the first stage, the algorithm sub-divides the current characteristics of the panel, and in the second stage of the algorithm, the MMPC method maintains the operating point at maximum power. The simulation and experimental results show that the proposed method has a faster dynamic response and low steady-state power ripple. The simulation and experimental results demonstrates that the MMPC method tracks the MPP more accurately and quickly than the MPC method under PSC.
引用
收藏
页码:1923 / 1947
页数:24
相关论文
共 50 条
  • [31] Modified Analytical Solution for Tracking Photovoltaic Module Maximum Power Point Under Partial Shading Condition
    Nezhad, Masoud Etezadi
    Asaei, Behzad
    Farhangi, Shahrokh
    2013 13TH INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING (EEEIC), 2013, : 182 - 187
  • [32] A Hybrid Maximum Power Point Tracking Approach for Photovoltaic Systems under Partial Shading Conditions Using a Modified Genetic Algorithm and the Firefly Algorithm
    Huang, Yu-Pei
    Chen, Xiang
    Ye, Cheng-En
    INTERNATIONAL JOURNAL OF PHOTOENERGY, 2018, 2018
  • [33] Bat algorithm based maximum power point tracking for photovoltaic system under partial shading conditions
    Kaced, Karim
    Larbes, Cherif
    Ramzan, Naeem
    Bounabi, Moussaab
    Dahmane, Zine Elabadine
    SOLAR ENERGY, 2017, 158 : 490 - 503
  • [34] A hybrid global maximum power point tracking method for photovoltaic arrays under partial shading conditions
    Huang, Chao
    Wang, Long
    Long, Huan
    Luo, Xiong
    Wang, Jenq-Haur
    OPTIK, 2019, 180 : 665 - 674
  • [35] Performance of smart maximum power point tracker under partial shading conditions of photovoltaic systems
    Eltamaly, Ali. M.
    JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY, 2015, 7 (04)
  • [36] A review of global maximum power point tracking techniques of photovoltaic system under partial shading conditions
    Belhachat, Faiza
    Larbes, Cherif
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2018, 92 : 513 - 553
  • [37] Accelerated Particle Swarm Optimization for Photovoltaic Maximum Power Point Tracking under Partial Shading Conditions
    Alshareef, Muhannad
    Lin, Zhengyu
    Ma, Mingyao
    Cao, Wenping
    ENERGIES, 2019, 12 (04)
  • [38] Model-based flexible power point tracking method for photovoltaic systems under partial shading conditions
    Wang, Manliang
    Gao, Bingtuan
    COMPUTERS & ELECTRICAL ENGINEERING, 2025, 123
  • [39] A review on maximum power point tracking for photovoltaic systems with and without shading conditions
    Ramli, Makbul A. M.
    Twaha, Ssennoga
    Ishaque, Kashif
    Al-Turki, Yusuf A.
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 67 : 144 - 159
  • [40] Power enhancement using improved maximum power point tracking for solar photovoltaic systems under partial shading
    Bhos, Chandrakant D.
    Sayyad, Javed
    Nasikkar, Paresh
    CLEAN ENERGY, 2022, 6 (06): : 810 - 816