6533b852fe1ef96bd12aaa8a

RESEARCH PRODUCT

Maximum Power Point Tracker for Standalone PV System Using Neural Networks

W. T. V. S. FernandoG. M. N. PriyashanthaM. A. N. SanjeewaMohan KolheK. M. S. Y. KonaraJ. W. G. S. Weerasinghe

subject

Maximum power principleDuty cyclebusiness.industryComputer scienceBoost converterPhotovoltaic systemElectrical engineeringResponse timebusinessPulse-width modulationMaximum power point trackingVoltage

description

In this work, designing and implementation of a maximum power point tracker (MPPT) based on an artificial neural network is proposed. The output voltage of the selected photovoltaic array is controlled by a DC to DC boost converter in a way that the PV array generates the available possible maximum power correspond to the available solar irradiance and temperature. The neural network (NN) is capable of forecasting the required terminal voltage of the PV array in order to generate the possible maximum power. The pulse width modulation (PWM) signal, which drives the boost converter, is generated through a raspberry pi according to the forecasted terminal voltage. The terminal voltage of the PV array is controlled by changing the duty ratio of the PWM signal accordingly. The impact of the implemented NN toward the response time and the accuracy is discussed. NN based MPPT can provide a reliable solution.

yearjournalcountryeditionlanguage
2019-01-01
https://doi.org/10.1007/978-981-13-6148-7_10