{'fraction_non_alphanumeric': 0.03010890454836643, 'fraction_numerical': 0.0064061499039077515, 'mean_word_length': 5.173913043478261, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Robust MPPT Method Based on AWILOG-ZALMS Algorithm for SPV Systems Under Various Loads and Non-Uniform Irradiance Conditions

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.