• Title of article

    A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability

  • Author/Authors

    Ahmed، نويسنده , , Jubaer and Salam، نويسنده , , Zainal، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2014
  • Pages
    13
  • From page
    118
  • To page
    130
  • Abstract
    AbstractObjectives ork proposes a Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search (CS) method. s acknowledged that CS exhibits several advantages which include fast convergence, higher efficiency using fewer tuning parameters. The paper outlines the concept of CS by highlighting the significance of the Lévy flight in influencing the algorithm’s convergence. The main equations that govern the behavior of the search are also explained. To justify CS as a viable MPPT option, a comprehensive assessment is carried out against two well established methods, namely Perturbed and Observed (P&O) and Particle Swarm Optimization (PSO). The evaluations include (1) gradual irradiance and temperature changes, (2) step change in irradiance and (3) rapid change in both irradiance and temperature. These tests are carried out for both large and medium-sized PV systems. Furthermore, the ability of the algorithm to handle the partial shading condition is demonstrated. s sults show that CS is capable of tracking MPP within 100–250 ms under various types of environmental change. Besides, the power loss in steady state due to MPP mismatch is only 0.000008%. Furthermore, it can handle the partial shading condition very efficiently. sion performs both P&O and PSO with respect to tracking capability, transient behavior and convergence. cal implications these excellent features, it is envisaged that the CS can be suitably used as a MPPT, particularly for large PV system.
  • Keywords
    Lévy flight , Cuckoo Search , Partial shading , Photovoltaic , MPPT , Soft Computing
  • Journal title
    Applied Energy
  • Serial Year
    2014
  • Journal title
    Applied Energy
  • Record number

    1607317