Mushtaq, Al-Duliamy and Hojabri, Mojgan and Hamdan, Daniyal and Ali Mahmood, Humada (2015) Maximum Power Prediction for PV System based on P&O Algorithm. Journal of Advanced & Applied Sciences (JAAS), 3 (4). pp. 113-118. ISSN 2289-6260. (Published)
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Abstract
This research presents a maximum power point tracking (MPPT) controller for PV systems is proposed. The developing of the proposed controller is based on conventional P&O algorithm and an Artificial Neural Network. The voltage of the optimum PV system is predicted by using ANN as a controller in order to get the maximum point of power (MPP). The three inputs for the modelled ANN are temperature coefficients, ambient temperature, and solar radiation. While, the output voltage represents the ANN output node. The simulation result shows that ANN much faster than P&Q algorithm in which the output voltage prediction is take 4.91 second as compared to conventional P&O algorithm which is 9.69 second.
Item Type: | Article |
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Uncontrolled Keywords: | ANN Controller, PV system, Perturbation, Observation algorithm, |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Faculty/Division: | Faculty of Electrical & Electronic Engineering |
Depositing User: | Mrs. Neng Sury Sulaiman |
Date Deposited: | 10 Sep 2015 06:32 |
Last Modified: | 09 Jan 2018 06:39 |
URI: | http://umpir.ump.edu.my/id/eprint/10161 |
Download Statistic: | View Download Statistics |
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