Maximum power point tracking of PV array under non-uniform irradiance using artificial neural network

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dc.contributor.authorRamana, V.V.
dc.contributor.authorJena, D.
dc.date.accessioned2026-02-06T06:39:33Z
dc.date.issued2015
dc.description.abstractThis paper presents a maximum power point tracking (MPPT) method for tracking the global peak (GP) of photovoltaic (PV) array under non-uniform irradiance using artificial neural network (ANN). A feed forward multilayer perceptron model with Levenberg - Marquardt back propagation algorithm is used for tracking the global peak. The MPPT algorithm takes irradiance of PV modules as input and gives duty ratio of boost converter as output. The MPPT presented using ANN is compared with conventional hill climbing (HC) method and the actual values obtained from the P-V characteristics. Root Mean Square Error (RMSE) of PV array output power is calculated for both hill climbing method and proposed ANN method. Finally, a qualitative comparison is made between hill climbing method and ANN method. © 2015 IEEE.
dc.identifier.citation2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems, SPICES 2015, 2015, Vol., , p. -
dc.identifier.urihttps://doi.org/10.1109/SPICES.2015.7091514
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/32374
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectartificial neural network
dc.subjectglobal peak
dc.subjectmaximum power point tracking
dc.subjectnonuniform irradiance
dc.subjectphotovoltaic
dc.titleMaximum power point tracking of PV array under non-uniform irradiance using artificial neural network

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