研究目的
Investigating the effectiveness of a hybrid intelligent GMPPT algorithm for partial shading PV system to improve the efficiency of PV systems under partial shading conditions.
研究成果
The proposed hybrid intelligent GMPPT algorithm effectively tracks the global maximum power point under partial shading conditions with reduced steady-state oscillation and improved convergence speed. It outperforms traditional PSO and P&O methods in most cases, indicating its potential for enhancing PV system efficiency.
研究不足
The study primarily focuses on simulation analysis and lacks extensive hardware platform verification. The proposed method's performance under extremely fast-changing environmental conditions is not thoroughly explored.
1：Experimental Design and Method Selection:
The study combines the basic PSO algorithm with the grouping idea of SFLA to ensure the differences among particles and the searching of global extremum. An adaptive speed factor is introduced to improve convergence. The variable step P&O method is used for accurate MPP tracking.
2：Sample Selection and Data Sources:
A PV array consisting of one PV module with 20 cells operating under various irradiance levels is considered.
3：List of Experimental Equipment and Materials:
Buck–Boost converter with specific parameters, PV panels under standard test condition.
4：Experimental Procedures and Operational Workflow:
The method involves initiating particles, updating their velocity and position based on fitness values, and using variable step P&O for dynamic MPP tracking.
5：Data Analysis Methods:
The performance is evaluated based on tracking speed and steady-state oscillations under fast variable PSCs.
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