Neural network based a two phase interleaved boost converter for photovoltaic system

Donny Radianto, Masahito Shoyama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

This paper presents Neural Network (NN) based A Two-Phase Interleaved Boost Converter (IBC) for Photovoltaic (PV) system. As known that this converter is the development of boost converter. In addition, it also functions to reduce output ripple current as well as to increase the output voltage of converter. This converter is driven by Pulse Width Modulation (PWM) which is governed by using controller based on NN. NN has two inputs including solar irradiance (G) and Temperature (T) and one output. The system is validated by a comparison between the proposed system with Fuzzy Logic Controller (FLC) in changing climate conditions. From the simulation results, the proposed system can provide higher voltage than FLC. In addition, the proposed system can shorten the steady state condition and can reduce voltage oscillations.

Original languageEnglish
Title of host publication3rd International Conference on Renewable Energy Research and Applications, ICRERA 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages430-434
Number of pages5
ISBN (Electronic)9781479937950
DOIs
Publication statusPublished - Jan 20 2014
Event3rd International Conference on Renewable Energy Research and Applications, ICRERA 2014 - Milwaukee, United States
Duration: Oct 19 2014Oct 22 2014

Publication series

Name3rd International Conference on Renewable Energy Research and Applications, ICRERA 2014

Other

Other3rd International Conference on Renewable Energy Research and Applications, ICRERA 2014
Country/TerritoryUnited States
CityMilwaukee
Period10/19/1410/22/14

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment

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