Research on MPPT Control Based on Improved Aquila Optimization Algorithm
Due to the uncertainty and intermittency of photovoltaic arrays,there are multiple peaks in the output of photovoltaic systems under local shadow conditions.The traditional Maximum Pow-er Tracking(MPPT)method cannot effectively track the maximum power point problem.To ad-dress this issue,a Sky Eagle Algorithm(IAO)based on Intermittency Chaos Mapping is proposed.By introducing chaotic mapping to improve the initialization population,the duty cycle is used as the control variable to achieve MPPT control.The final simulation shows that compared with the original algorithm,the improved Tianying algorithm significantly improves the convergence speed and accuracy on the basis of MPPT application,and improves the power generation efficiency.
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维普
