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Intelligent Power Harvesting in Grid-tied PV Systems Using Adaptive Grey Wolf Optimization Based MPPT Control Under Partial Shading Conditions

Students & Supervisors

Student Authors
Nasif Hannan
Bachelor of Science in Electrical & Electronic Engineering, FE
Tashawar Muhammad Rasha
Debashish Kumar Ghosh
Bachelor of Science in Electrical & Electronic Engineering, FE
Md Ismail Hossain
Bachelor of Science in Electrical & Electronic Engineering, FE
Supervisors
Abu Shufian
Lecturer, Faculty, FE
Md Sajid Hossain
Assistant Professor, Faculty, FE

Abstract

In this paper, a Grey Wolf Optimization (GWO)-based Maximum Power Point Tracking (MPPT) controller is proposed for real-time power optimization in a residential on-grid photovoltaic (PV) system. The developed approach addresses the challenges posed by partial shading conditions (PSC), which often lead to multiple local maxima in the power-voltage curve. Unlike traditional MPPT methods, the GWO algorithm demonstrates a highly efficient and adaptive search mechanism that accurately identifies the Global Maximum Power Point (GMPP). The system achieves a peak power output of 395–400 W with a rapid tracking time of ≤0.20 seconds and MPPT efficiency exceeding 97.3%. Voltage stability is maintained within ±1.2%, and the duty cycle converges within a tight range of 0.55–0.62, minimizing switching losses and ensuring consistent performance. This research presents a comprehensive performance evaluation, confirming that the proposed GWO-based MPPT not only enhances energy extraction but also improves overall system responsiveness and reliability under dynamic environmental conditions.

Keywords

PV power optimization GWO MPPT PSC residential GMPP efficiency.

Publication Details

  • Type of Publication: Conference 
  • Conference Name: 2nd International Conference on Next-Generation Computing, IoT and Machine Learning (NCIM 2025)
  • Date of Conference: 27/06/2025 - 27/06/2025
  • Venue: Gazipur
  • Organizer: IEEE
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