PSO-Based Adaptive Perturb and Observe MPPT Technique for Photovoltaic Systems

  • Nashwa Ahmad Kamal
  • Ahmad Taher AzarEmail author
  • Ghada Said Elbasuony
  • Khaled Mohamad Almustafa
  • Dhafer Almakhles
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1058)


The classical method of perturb and observe (P&O) is mostly utilized because of it is simple technique, ease of implementation and low cost. Although, it has high oscillations around maximum power point (MPP) at steady state due to perturbation and challenge between step size and the convergence time. To avoid the drawbacks of classical P&O methods, this paper presents adaptive P&O using optimized proportional integral (PI) controller by particle swarm optimization (PSO) algorithm. To evaluate the proposed method, a PV system model is designed with different scenarios under various weather conditions. For each scenario, simulations are carried out and the results are compared with the other classical P&O MPPT methods. The results revealed that the proposed PSO-PI-P&O MPPT method improved the tracking performance, response to the fast changing weather conditions and also has less oscillation around MPP as compared to the classical P&O methods.


Photovoltaic systems Renewable energy control Maximum power point tracking Particle Swarm Optimization 



The authors would like to thank Prince Sultan University, Riyadh, KSA for supporting this work.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Nashwa Ahmad Kamal
    • 1
  • Ahmad Taher Azar
    • 2
    • 3
    Email author
  • Ghada Said Elbasuony
    • 1
  • Khaled Mohamad Almustafa
    • 4
  • Dhafer Almakhles
    • 2
  1. 1.Electrical Power and Machine Department, Faculty of EngineeringCairo UniversityGizaEgypt
  2. 2.College of EngineeringPrince Sultan UniversityRiyadhKingdom of Saudi Arabia
  3. 3.Faculty of Computers and Artificial IntelligenceBenha UniversityBenhaEgypt
  4. 4.College of Computer Science and Information Systems (CCIS), Prince Sultan UniversityRiyadhKingdom of Saudi Arabia

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