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This work aims to enhance Maximum Power Point Tracking (MPPT) in photovoltaic systems using a novel algorithm.

June 7, 2026

A swarm-based soft computing approach for harvesting maximum power in practical photovoltaic system

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Randomized trial demonstrates improved power tracking efficiency in photovoltaic systems, suggesting advancements in renewable energy technology.

This work aims to enhance Maximum Power Point Tracking (MPPT) in photovoltaic systems using a novel algorithm.
Proposed Zone Segregated Adaptive Particle Swarm Optimization (ZSAPSO) for MPPT.
Performed sensitivity analysis to optimize ZSAPSO performance.
Simulated and authenticated outcomes through MATLAB/SIMULINK and practical setup.
Achieved tracking efficiency of 99.987% under uniform irradiance with 0.037% steady-state error.
Under partial shading, ZSAPSO reached 99.977% efficiency with a minimum error of 0.025%.
Demonstrated faster convergence than other swarm-based MPPT techniques.

Mukherjee et al. (2026) studied this question.

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Randomized trial demonstrates improved power tracking efficiency in photovoltaic systems, suggesting advancements in renewable energy technology.