A new RBFN based MPPT controller for grid-connected PEMFC system with high step-up three-phase IBC

被引：41

作者：

Reddy, K. Jyotheeswara ^{[1
]}

Sudhakar, N. ^{[1
]}

机构：

[1] VIT, Sch Elect Engn, Vellore, Tamil Nadu, India

来源：

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY | 2018年 / 43卷 / 37期

关键词：

PEMFC; High step-up IBC; MPPT; RBFN; Grid-connected system; FUEL-CELL; MAXIMUM POWER; PHOTOVOLTAIC SYSTEM; FUZZY-LOGIC; OPTIMIZATION; ALGORITHM; HYBRID; SOLAR; MODEL;

D O I：

10.1016/j.ijhydene.2018.07.177

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

摘要：

Extraction of maximum power from a proton exchange membrane fuel cell (PEMFC) power source is necessary for its economical and optimal utilization. In this paper, a neural network based maximum power point tracking (MPPT) controller is proposed for the grid-connected PEMFC system. Radial basis function network (RBFN) algorithm is implemented in the neural network controller to extract the maximum power from PEMFC. A high step-up three-phase interleaved boost converter (IBC) is also designed in order to reduce the current ripples coming out from the PEMFC. Interleaving technique provides high power capability and reduces the voltage stress on the power semiconductor devices. The performance analysis of the proposed RBFN MPPT controller is analyzed in MATLAB/Simulink platform for both standalone as well as for the grid-connected PEMFC system. (C) 2018 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

引用

页码：17835 / 17848

页数：14

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