Enhanced MPPT Strategy for Solar PV under Partial Shading using Improved Grey Wolf Optimization
This paper proposes an Improved Grey Wolf Optimization (IGWO) algorithm to address the challenge of reduced Maximum Power Point Tracking (MPPT) efficiency in photovoltaic (PV) systems under partial shading conditions. The IGWO algorithm enhances the standard Grey Wolf Optimization (GWO) by updating the alpha vector with each iteration, aiming to improve convergence rates and reduce the risk of local optima. Simulation results using MATLAB-SIMULINK on a single-diode Solar-PV system demonstrate that the IGWO algorithm outperforms traditional GWO-based MPPT algorithms by overcoming reduced tracking efficiency and steady-state oscillations. The IGWO algorithm leads to improved tracking speed and overall performance under partial shading conditions.
Authors
- Wencong Su (ORCID: https://orcid.org/0000-0003-1482-3078)
- Gajendra Singh Chawda (ORCID: https://orcid.org/0000-0001-8244-1755)
- Mengqi Wang (ORCID: https://orcid.org/0000-0003-1979-2565)
Institutions
- University of Michigan–Dearborn (US)
Publication Details
- Published
- 2024-11-03
- DOI
- https://doi.org/10.1109/iecon55916.2024.10905448
- Citations
- 1
- Primary Topic
- Photovoltaic System Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.10