Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8954950 | International Journal of Hydrogen Energy | 2018 | 14 Pages |
Abstract
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.
Keywords
Related Topics
Physical Sciences and Engineering
Chemistry
Electrochemistry
Authors
K. Jyotheeswara Reddy, N. Sudhakar,