A new maximum power point control algorithm of photovoltaic generation system

被引:0
作者
Bian, Xiaoxue [1 ]
Sun, Xiujuan [1 ]
Yang, Zhuo [1 ]
机构
[1] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao, Peoples R China
关键词
Solar power generation; multi-peak; particle swarm algorithm; Newton method;
D O I
10.1080/21642583.2018.1558419
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Due to the severe environmental changes, especially in the context of the greatly change of the sunlight, the output power of the solar power system will be unstable. In the case of partial obstruction, the equivalent characteristic curves of the photovoltaic panel show a multi-peak state, traditional maximum power control technology is prone to misjudgment and cannot find the maximum power point (MPP). In order to solve this problem, a Newton method based on particle swarm optimization (PSO) is proposed to control the multi-peak MPP. The algorithm will firstly optimize the inertia weight of the particle swarm algorithm, then it will use the optimized particle swarm algorithm to search for the multi-peak MPP. The Newton method will rapidly solve the maximum value to achieve multi-peak MPP tracking when curves approaching to the maximum value. Construction of the boost chopper circuit, which was compared with the particle swarm algorithm and Newton method, was simulated under different light intensities by the simulation softwares such as Simulink and Matlab. The results show that Newton method based on the PSO can quickly find the maximum power with characteristics of good convergence speed and accuracy.
引用
收藏
页码:333 / 338
页数:6
相关论文
共 50 条
  • [31] Improved virtual synchronous generator control strategy for distributed photovoltaic power system
    Gao C.
    Liu X.
    Meng Z.
    [J]. Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2021, 42 (02): : 376 - 382
  • [32] Novel Transformerless Grid-Connected Power Converter With Negative Grounding for Photovoltaic Generation System
    Shen, Jia-Min
    Jou, Hurng-Liahng
    Wu, Jinn-Chang
    [J]. IEEE TRANSACTIONS ON POWER ELECTRONICS, 2012, 27 (04) : 1818 - 1829
  • [33] Particle Swarm Optimization Algorithm in Power Line Overhaul System Control
    Liu, Jia
    Li, Yang
    Gao, Liqun
    [J]. 2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11, 2008, : 2348 - 2350
  • [34] Energy management of new energy ships based on maximum power point tracking of particle swarm optimization
    Wu, Jie
    Zhi, Pengfei
    Zhu, Wanlu
    Jin, Chunpeng
    [J]. PROCEEDINGS OF 2022 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (IEEE ICMA 2022), 2022, : 59 - 64
  • [35] Modeling Maximum Power Point Tracking Efficiency for PV Systems
    Westbrook, Owen W.
    [J]. 2015 IEEE 42ND PHOTOVOLTAIC SPECIALIST CONFERENCE (PVSC), 2015,
  • [36] Grid-tied Modular and Scalable Photovoltaic Distributed Maximum Power Point Tracking System with Storage at Module Level Using Non-Isolated Three-Port Converters
    Gonzalez, Ander
    Lopez-Erauskin, Ramon
    Gyselinck, Johan
    [J]. 2018 20TH EUROPEAN CONFERENCE ON POWER ELECTRONICS AND APPLICATIONS (EPE'18 ECCE EUROPE), 2018,
  • [37] ANFIS-based Maximum Power Point Tracking Control of PV Modules with DC-DC Converters
    Chu, Yuan-Ting
    Yuan, Li-Qiang
    Chiang, Hsin-Han
    [J]. 2015 18TH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS), 2015, : 692 - 697
  • [38] Solar photovoltaic power generation in Iran: Development, policies, and barriers
    Gorjian, Shiva
    Zadeh, Babak Nemat
    Eltrop, Ludger
    Shamshiri, Redmond R.
    Amanlou, Yasaman
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2019, 106 : 110 - 123
  • [39] Metaheuristic searching genetic algorithm based reliability assessment of hybrid power generation system
    Abdalla, Ahmed N.
    Nazir, Muhammad Shahzad
    Jiang, MingXin
    Kadhem, Athraa Ali
    Wahab, Noor Izzri Abdul
    Cao, Suqun
    Ji, Rendong
    [J]. ENERGY EXPLORATION & EXPLOITATION, 2021, 39 (01) : 488 - 501
  • [40] Battery Energy Storage Station (BESS)-Based Smoothing Control of Photovoltaic (PV) and Wind Power Generation Fluctuations
    Li, Xiangjun
    Hui, Dong
    Lai, Xiaokang
    [J]. IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2013, 4 (02) : 464 - 473