A Review On Artificial Intelligence-Based MPPT And Total Harmonic Distortion Reduction In PV Grids: Insights For Cognitive Adaptation In Reattach Therapy
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Abstract
The increasing use of photovoltaic (PV) systems for sustainable energy faces two major challenges: tracking the global maximum power point (GMPP) during partial shading conditions (PSC) and mitigating Total Harmonic Distortion (THD) caused by fluctuating solar irradiance. These challenges impact the efficiency and performance of PV systems integrated into grid networks. Artificial Intelligence (AI) has proven effective in optimizing Maximum Power Point Tracking (MPPT), addressing both GMPP tracking and THD reduction. Interestingly, AI's adaptive strategies in PV systems parallel cognitive adaptation techniques in ReAttach Therapy, which fosters neuroplasticity and cognitive flexibility in individuals with developmental diversities. Both frameworks rely on timely, dynamic adjustments to optimize outcomes, whether in energy management or cognitive rehabilitation. This review examines AI-based MPPT algorithms and their role in THD reduction, drawing parallels with ReAttach Therapy’s adaptive processes. Just as adaptive filters (AF) reduce noise and disturbances in PV systems, ReAttach techniques help individuals adapt to sensory stimuli and improve emotional regulation. The paper highlights how AI-based solutions can inspire advancements in therapeutic approaches by integrating adaptive strategies to enhance performance in both fields. By providing a multidisciplinary perspective, this review offers new insights into selecting optimal AI-based MPPT methods while promoting adaptive strategies applicable in both technological and therapeutic contexts.
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