A Robust MPPT Method Based on AWILOG-ZALMS Algorithm for SPV Systems Under Various Loads and Non-Uniform Irradiance Conditions

Haider A. Mohamed Kazim, I. Abdel-Qader
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Abstract

A robust Zero-Attracting LMS (ZALMS) time-adjustment stepsize adaptation technique for the conventional P&O MPPT method of PV systems is presented. We aimed in this work to accurately attain the maximum power point of the PV systems under various loads and irradiation conditions using Absolute Weighted Input using Log (AWILOG) function for variable stepsize (VSS) ZALMS, i.e. AWILOG-VSS-ZALMS algorithm from [21]. In this work, the filter coefficients adaptation strategy used is based on the L1-norm constraint instead of the L0-norm as was proposed in the AWILOG-VSS-RZALMS [21]. We present a comparative analysis using different connected load types under several patterns of non-uniform irradiation conditions. Results show that in comparison with the conventional method, our algorithm delivers faster convergence and a more rapid response to environmental variations while still reducing steady-state power oscillations. The comparative analysis between both methods using L1-norm versus L0-norm showing their tracking behavior in terms of speed and performance is also presented. Results show that this proposed work, when compared to the AWILOG-VSS-RZALMS algorithm in [19], delivers a relatively slower dynamic response but it delivers a reduction in computational complexity making it more suitable for practical application. In all, the algorithm is robust, and we aim in the future to implement it in real-time systems.
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基于AWILOG-ZALMS算法的SPV系统多负荷非均匀辐照鲁棒MPPT方法
提出了一种鲁棒的零吸引LMS (ZALMS)时调整步长自适应技术,用于光伏系统的常规P&O MPPT方法。在这项工作中,我们的目标是使用可变步长(VSS) ZALMS的绝对加权输入(AWILOG)函数,即[21]中的AWILOG-VSS-ZALMS算法,准确地获得光伏系统在各种负载和辐照条件下的最大功率点。在这项工作中,使用的滤波器系数自适应策略基于l1范数约束,而不是AWILOG-VSS-RZALMS[21]中提出的l0范数约束。我们提出了在几种不均匀辐照条件下使用不同连接负载类型的比较分析。结果表明,与传统方法相比,该算法收敛速度更快,对环境变化的响应速度更快,同时仍能减少稳态功率振荡。还介绍了两种方法之间的比较分析,分别使用l1规范和l0规范,显示了它们在速度和性能方面的跟踪行为。结果表明,与[19]中的AWILOG-VSS-RZALMS算法相比,本文提出的工作提供了相对较慢的动态响应,但降低了计算复杂度,使其更适合实际应用。总之,该算法是鲁棒的,我们的目标是在未来的实时系统中实现它。
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