2022
DOI: 10.1007/s11831-022-09803-x
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Nature-Inspired Optimization Algorithms in Solving Partial Shading Problems: A Systematic Review

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Cited by 20 publications
(4 citation statements)
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“…Furthermore, if algorithm designers fail to account for these changes, a given working condition may fail. One can deduce that the most typical obstacles are the nonlinearity of PV features, variations in ambient conditions, and system functioning conditions [53][54][55][56][57][58][59][60].…”
Section: A Challenges Of Mppt Algorithmsmentioning
confidence: 99%
“…Furthermore, if algorithm designers fail to account for these changes, a given working condition may fail. One can deduce that the most typical obstacles are the nonlinearity of PV features, variations in ambient conditions, and system functioning conditions [53][54][55][56][57][58][59][60].…”
Section: A Challenges Of Mppt Algorithmsmentioning
confidence: 99%
“…The global methods usually combine ICP with natureinspired optimization algorithms [24,25], such as particle swarm optimization [26,27], genetic algorithm [28,29], simulated annealing method [30,31], discrete cat swarm optimization [32], and coati optimization algorithm [33]. These methods can make ICP to jump out local minima in a probability, but it cannot theoretically guarantee the global optimal solution.…”
Section: Wearmentioning
confidence: 99%
“…Many tracking approaches have been, recently, introduced to attain the optimal power of the PV system, which has drawn considerable interest from researchers 16 , 17 . Two MPPT categories are broadly classified; conventional and soft computing MPPT algorithms as depicted in Fig.…”
Section: Introductionmentioning
confidence: 99%