Cuckoo Search-Based MPPT Design for PV Optimization Under Partial Shading

Sajid Ibrahim; Azriyenni  Azhari Zakri; Boy Ihsan; Beenish  Sultana

doi:10.31258/ijeepse.9.3.184-201

Sajid Ibrahim Universitas Riau, Pekanbaru, Indonesia
Azriyenni Azhari Zakri Universitas Riau, Pekanbaru, Indonesia
Boy Ihsan Universitas Riau, Pekanbaru, Indonesia
Beenish Sultana NED University of Engineering and Technology, Karachi, Pakistan

DOI: https://doi.org/10.31258/ijeepse.9.3.184-201

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Keywords: Buck-Boost Converter, Cuckoo Search, MPPT, Partial Shading, Photovoltaic

Abstract

Partial shading conditions (PSC) give a major challenge to photovoltaic (PV) systems by producing multiple local maximum power points (LMPPs) and a global maximum power point (GMPP), which can cause conventional maximum power point tracking (MPPT) methods such as Perturb and Observe (P&O) to converge at an LMPP. This study aims to design and evaluate a Cuckoo Search (CS) based MPPT method using a buck-boost converter for PV battery charging under PSC. The proposed method uses Lévy flight and nest-updating mechanisms to optimize the converter duty cycle. CS and P&O were compared via MATLAB/Simulink simulations under uniform irradiance and PSC scenarios. The optimal CS parameters were obtained as Pa = 0.25, α = 0.4, and β = 1.5. Under uniform irradiance, P&O achieved 99.90% tracking efficiency with a 0.028 s tracking time, while CS achieved 99.95% efficiency with a 0.148 s tracking time. Under PSC, P&O achieved 52.55-99.85% efficiency and failed to track the GMPP under complex shading, whereas CS consistently tracked the GMPP with 99.30-99.91% efficiency. The average overall efficiency was 73.24% for P&O and 93.35% for CS. These results demonstrate that CS is able to provide reliable GMPP tracking and high overall system efficiency under PSC.

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