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Abstract
Abstract In scenarios of partial shading, photovoltaic array output characteristics can exhibit multiple peaks, which can cause traditional maximum power point tracking (MPPT) algorithms to get stuck in local optima. An enhanced sparrow search algorithm for MPPT is introduced to enhance the efficiency of photovoltaic systems. This improved approach utilizes Tent chaotic mapping for population initialization and incorporates an adaptive weight factor to refine convergence precision. Simulation results demonstrate that the improved sparrow search algorithm, compared to the conventional version, offers superior convergence speed and stability when applied to multi-peak MPPT scenarios.
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