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@article{165944,
        author = {Eva Sharma and Dr. Vikramaditya Dave and Vishvraj singh rathore},
        title = {Unveiling global MPP: ACO-driven MPPT strategy for partially shaded PV arrays},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {1},
        pages = {2108-2113},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=165944},
        abstract = {Maximizing the efficiency of photovoltaic (PV) arrays requires operation at their maximum power point (MPP). Traditional maximum power point tracking (MPPT) techniques perform well under uniform irradiance but falter when partial shading introduces multiple MPPs, often failing to identify the global MPP. To tackle this issue, we introduce an ant colony optimization (ACO)-based MPPT scheme for PV systems. This heuristic algorithm not only ensures the identification of the global MPP but also simplifies the control scheme and reduces system costs. We validated the feasibility of the proposed method through simulations under various shading patterns and compared its performance to that of traditional MPPT techniques, such as Constant Voltage Tracking (CVT), Perturb and Observe (P&O), and Particle Swarm Optimization (PSO).Results indicate that the proposed ACO-based algorithm effectively tracks the global MPP and exhibits robustness across different shading scenarios, thus offering a reliable and cost-effective solution for enhancing the efficiency of PV systems.},
        keywords = {Ant Colony Optimization, Enhanced System Efficiency, Maximum Power Point Tracking, Partial Shading Mitigation, Photovoltaic Optimization.},
        month = {June},
        }