A Comparative Simulation Study of Modified Incremental Conductance and Perturb-and-observe Algorithms for Enhanced Efficiency under Dynamic Environmental Conditions
J. Environ. Nanotechnol., Volume 15, No 1 (March 2026) pp. 35-47
Abstract
This study presents a nanomaterial-engineered solar energy conversion and storage system that integrates a quasi-Z-source converter with adaptive maximum power point tracking (MPPT) algorithms, namely Modified Incremental Conductance (MIC) and Modified Perturb-and-Observe (M-P & O), to enhance photovoltaic (PV) performance under dynamic irradiance conditions. The overall system behaviour and control effectiveness are systematically evaluated using MATLAB/Simulink-based simulations. Simulation results demonstrated that the MIC algorithm offers superior voltage stability, faster dynamic response, and higher tracking accuracy compared to the M-P & O approach. It achieved 1.6 kW additional simulated power output at a standard operating temperature of 25 ℃. The proposed PV module employed a hybrid nanomaterial configuration in which quantum dots and graphene derivatives are embedded within the photoactive layer to broaden spectral absorption and improve charge carrier mobility, while metal oxide nanoparticles such as TiO2 and ZnO enhance interfacial charge separation and suppressed the recombination losses. These nanomaterial-induced modifications result in nonlinear and dynamically varying current–voltage characteristics, thereby necessitating adaptive MPPT control. The dynamic step-size adjustment mechanism implemented in the MIC algorithm effectively accommodated these variations, enabling stable and efficient energy extraction. Overall, simulation-based findings indicate an efficiency improvement of approximately 6–8%, demonstrating a scalable and sustainable pathway for high-performance solar energy systems.
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