Optimized Nonlinear PID Control for Maximum Power Point Tracking in PV Systems Using Particle Swarm Optimization

被引:1
|
作者
Zambou, Maeva Cybelle Zoleko [1 ]
Kammogne, Alain Soup Tewa [1 ]
Siewe, Martin Siewe [2 ]
Azar, Ahmad Taher [3 ,4 ]
Ahmed, Saim [3 ,4 ]
Hameed, Ibrahim A. [5 ]
机构
[1] Univ Dschang, Fac Sci, Dept Phys, Lab Condensed Matter Elect & Signal Proc LAMACETS, POB 67, Dschang, Cameroon
[2] Univ Yaounde I, Fac Sci, Dept Phys, Lab Mech Mat & Struct, POB 812, Yaounde, Cameroon
[3] Prince Sultan Univ, Coll Comp & Informat Sci, Riyadh 11586, Saudi Arabia
[4] Prince Sultan Univ, Automated Syst & Soft Comp Lab ASSCL, Riyadh 11586, Saudi Arabia
[5] Norwegian Univ Sci & Technol, Dept ICT & Nat Sci, Larsgardsvegen 2, N-6009 Alesund, Norway
关键词
photovoltaic system; perturb and observe; discrete nonlinear PID; particle swarm optimization; maximum power point tracking; MPPT;
D O I
10.3390/mca29050088
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper proposes a high-performing, hybrid method for Maximum Power Point Tracking (MPPT) in photovoltaic (PV) systems. The approach is based on an intelligent Nonlinear Discrete Proportional-Integral-Derivative (N-DPID) controller with the Perturb and Observe (P&O) method. The feedback gains derived are optimized by a metaheuristic algorithm called Particle Swarm Optimization (PSO). The proposed methods appear to present adequate solutions to overcome the drawbacks of existing methods despite various weather conditions considered in the analysis, providing a robust solution for dynamic environmental conditions. The results showed better performance and accuracy compared to those encountered in the literature. We also recall that this technique provides a systematic design procedure in the search for the MPPT in photovoltaic (PV) systems that has not yet been documented in the literature to the best of our knowledge.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] A Modified Particle Swarm Optimization based Maximum Power Point Tracking for PV Systems
    Alshareef, Muhannad
    Lin, Zhengyu
    2018 53RD INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE (UPEC), 2018,
  • [2] Particle Swarm Based Optimization Algorithm for Maximum Power Point Tracking in Photovoltaic (PV) Systems
    Gavali, Saurabh
    Deshpande, Amruta
    2017 2ND IEEE INTERNATIONAL CONFERENCE ON RECENT TRENDS IN ELECTRONICS, INFORMATION & COMMUNICATION TECHNOLOGY (RTEICT), 2017, : 1583 - 1586
  • [3] Application of Particle Swarm Optimization for Maximum Power Point Tracking in PV System
    Balamurugan, M.
    Narendiran, S.
    Sahoo, Sarat Kumar
    Das, Raja
    Sahoo, Ashwin Kumar
    2016 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL ENERGY SYSTEMS (ICEES), 2016, : 35 - 38
  • [4] Maximum Power Point Tracking for Single Diode PV Model using Particle Swarm Optimization
    Abd Rahman, Nadia Hanis
    Romli, Muhamad Shafiq
    Ismail, Bazilah
    Alhamrouni, Ibrahim
    5TH INTERNATIONAL CONFERENCE ON GREEN DESIGN AND MANUFACTURE 2019 (ICONGDM 2019), 2019, 2129
  • [5] Accelerated Particle Swarm Optimization Algorithm for Maximum Power Point Tracking in Partially Shaded PV Systems
    Subha, R.
    Himavathi, S.
    2016 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL ENERGY SYSTEMS (ICEES), 2016, : 232 - 236
  • [6] Application of Particle Swarm Optimization for Maximum Power Point Tracking of PV System with Direct Control Method
    Ishaque, Kashif
    Salam, Zainal
    Shamsudin, Amir
    IECON 2011: 37TH ANNUAL CONFERENCE ON IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2011, : 1214 - 1219
  • [7] Maximum Power Point Tracking for a PV System Using Tuned Support Vector Regression by Particle Swarm Optimization
    Abo-Khalil, Ahmed G.
    JOURNAL OF ENGINEERING RESEARCH, 2020, 8 (04): : 139 - 152
  • [8] Maximum power point tracking control of photovoltaic systems using a hybrid improved whale particle swarm optimization algorithm
    Zhang, Lianghao
    Wang, Shuang
    Ni, Zihao
    Li, Fashe
    ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS, 2025, 47 (01) : 1789 - 1803
  • [9] Adaptability Analysis of Particle Swarm Optimization Variants in Maximum Power Tracking for Solar PV Systems
    Dharshan, B. G.
    Rajasekar, N.
    Sankarkumar, R. Srinivasa
    INTELLIGENT COMPUTING TECHNIQUES FOR SMART ENERGY SYSTEMS, 2020, 607 : 397 - 409
  • [10] PV maximum power-point tracking using modified particle swarm optimization under partial shading conditions
    Ibrahim A.-W.
    Shafik M.B.
    Ding M.
    Sarhan M.A.
    Fang Z.
    Alareqi A.G.
    Almoqri T.
    Al-Rassas A.M.
    Shafik, M.B. (muhammedshafiq@yahoo.com), 1600, Institute of Electrical and Electronics Engineers Inc. (06): : 106 - 121