Particle swarm optimization for enhanced maximum power point tracking: design and implementation in Proteus

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Abstract

This study introduces a photovoltaic (PV) system model tailored for PV design, incorporating a particle swarm optimization (PSO) MPPT technique to achieve optimal efficiency, swift responsiveness, and cost-effectiveness. To initiate, a PV module model is formulated within Proteus using SPICE coding. Subsequently, an experimental test setup is deployed to authenticate and validate the model. Following this, a PSO-based MPPT algorithm is proposed, which overcomes the limitations of conventional perturb and observe (P&O) and incremental conductance MPPT methods, notably reducing the reliance on mathematical divisions. To substantiate the effectiveness of the proposed approach, both methodologies are implemented on an affordable Arduino Uno platform utilizing the simulated PV module model. The outcomes highlight that the PSO-based MPPT algorithm excels in terms of rapid response (0.09 s), minimal steady-state oscillation, and an impressive 99 percent efficiency.

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Vishnu Priya, M., & Anandha Kumar, G. (2024). Particle swarm optimization for enhanced maximum power point tracking: design and implementation in Proteus. International Journal of Power Electronics and Drive Systems, 15(1), 491–497. https://doi.org/10.11591/ijpeds.v15.i1.pp491-497

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