Maximum power point tracking algorithm of PV system based on irradiance estimation and multi-Kernel extreme learning machine

2021 ◽  
Vol 44 ◽  
pp. 101090
Author(s):  
Zongkui Xie ◽  
Zhongqiang Wu
Author(s):  
C. Pavithra ◽  
Pooja Singh ◽  
Venkatesa Prabhu Sundramurthy ◽  
T.S. Karthik ◽  
P.R. Karthikeyan ◽  
...  

2018 ◽  
Vol 9 (2) ◽  
pp. 88-91
Author(s):  
Wolfgang Jalma

Maximum Power Point Tracking is a method to obtain maximum harvest of PV solar cell. Due to PV nonlinearity, a lot of novel approach has been. One of the most prominence is neural network, that usually can solve this nonlinearity formulation, although needs relatively longer time in order to train, making it unfeasible for real implementation. This research tried to accelerate the training of the neural network based MPPT, using Extreme Learning Machine, with quite promising results. Index Terms—Maximum Power Point Tracking, Neural Network, PV Solar Cell, Extreme Learning machine.


Author(s):  
Imad A. Elzein ◽  
Yuri N. Petrenko

In this article an extended literature surveying review is conducted on a set of comparative studies of maximum power point tracking (MPPT) techniques.  Different MPPT methods are conducted with an ultimate aim of how to be maximizing the PV system output power by tracking Pmax in a set of different operational circumstances. In this paper maximum power point tracking, MPPT techniques are reviewed on basis of different parameters related to the design simplicity and or complexity, implementation, hardware required, and other related aspects.


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