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Comparative Study of Applications of Cr Principle in Maximum Power Point Tracking of Solar PV Array


Amit Chouksey , Research Scholar,JVWU Jaipur,; Dr. S. S. Awasthi, JVWU; Dr. S. K. Singh, JVWU


PV Array, MPPT, Perturb & Observe Algorithm, Fuzzy Logic, Simulink


The investigations on the photovoltaic (PV) control age are widely expanding, since it is considered as a basically endless and comprehensively accessible vitality asset. In any case, the yield intensity of the photovoltaic modules relies upon sun oriented radiation and temperature of the sun oriented cells. Thusly, to augment the productivity of the sustainable power source framework, it is important to track the most extreme power purpose of the PV exhibit and influence the cluster to work close it. Greatest power task is a testing issue, since it requires that the framework stack is equipped for utilizing all power accessible from the PV framework constantly. The I-V normal for the heap must meet the focal point of most extreme power focuses on the I-V qualities of the PV exhibit for fluctuating insolation and temperature levels. Fluffy Cognitive Networks (FCN) have been proposed as an operational augmentation of Fuzzy Cognitive Maps (FCM), which work in persistent connection with the framework they depict and might be utilized to control it. In this section FCN is utilized to build a most extreme power point tracker (MPPT), which may work in participation with a fluffy MPPT controller. The proposed conspire outflanks other existing MPPT plans of the writing giving great most extreme power activity of any PV exhibit under various conditions, for example, changing insolation and temperature. Additionally it can adjust to various changes that may occur amid the existence cycle of the PV module, for example, a demolished cell of the PV exhibit.

Other Details

Paper ID: IJSRDV6I60131
Published in: Volume : 6, Issue : 6
Publication Date: 01/09/2018
Page(s): 267-270

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