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@article{185663,
        author = {Dharavath Ramesh Nayak and K. Pandu and MADARAM VIKRAMGOUD and Dr. P. Umapathi Reddy},
        title = {A Comparative Performance Analysis of ANN Algorithms for MPPT Energy Harvesting In Solar System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {5},
        pages = {2348-2353},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185663},
        abstract = {The generation of clean power has placed solar photovoltaic (PV) systems in the range of very high-demand clean energy sources. However, the capacity of the sunlight and temperature to variation in efficiency requires effective Maximum Power Point Tracking (MPPT) plans. Comparative analysis of artificial neural network (ANN)-based MPPT algorithms and other conventional algorithms such as Perturb and Observe, Incremental Conductance and Fuzzy Logic Control has been given in this paper. Accuracy, response time and stability: These algorithms are tested on MATLAB/Simulink. The results show that ANN-based approaches are more suitable in the application of solar energy in a predictable manner, as they have higher tracking and adaptability to evolving circumstances. Results provide useful data on the selection of the appropriate MPPT strategies to enhance the efficiency and sustainability of PV systems.},
        keywords = {: Maximum Power Point Tracking (MPPT), artificial neural network (ANN), solar photovoltaic (PV), Fuzzy Logic Control.},
        month = {October},
        }