Modelling and analysis of DC-DC converters with AI based MPP tracking approaches for grid-tied PV-fuel cell system

• Published in: Electric power systems research Vol. 216; p. 109053
• Main Authors: Reddy, B Raja Sekhar, Reddy, V.C Veera, Kumar, M. Vijaya
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-03-2023
• Subjects: DC-DC converters; Grid integrated system; MPPT; Novel radial basis function network; PV system, PEMFC; Grid integrated system; DC-DC converters; MPPT; Novel radial basis function network; PV system, PEMFC
• ISSN: 0378-7796; 1873-2046
• DOI: 10.1016/j.epsr.2022.109053

•This study focuses on a hybrid power system that combines renewable energy sources are photovoltaic (PV) and fuel cell.•To maximise the power at different solar irradiation levels and PEMFC (proton exchange membrane fuel cell) temperatures, fuzzy logic controllers (FLC) for solar photovoltaics and novel radial basis function (RBF) neural network based maximum power point (MPP) tracking approach for fuel cells are developed.•In addition, a switched inductor based voltage multiplier cell (VMC) for fuel cells has been designed, which provides a higher voltage gain than a conventional boost converter.•The performance of the proposed system is compared with the modified P&O MPPT technique is used for both PV and fuel cell.•The proposed converter is implemented as a prototype model and tested in the laboratory setup to confirm the efficiency of the designed converter.
It is required to combine various energy sources and power electronic converters in order to adequately fulfil the load needs under a variety of natural circumstances. This study focuses on a hybrid power system that combines renewable energy sources are photovoltaic (PV) and Fuel cell. The Grid integrated system is more sustainable when PV modules and fuel cells are combined together since the system can meet required load even when there is no solar. To maximise the power at different solar irradiation levels and PEMFC (proton exchange membrane fuel cell) temperatures, fuzzy logic controllers (FLC) for solar photovoltaics and novel radial basis function (RBF) neural network based maximum power point (MPP) tracking approaches for fuel cells are developed. In addition, a switched Inductor based Voltage Multiplier Cell (VMC) for fuel cells has been designed, which provides a higher voltage gain than a conventional Boost converter. The suggested system's dynamic behaviour is examined under various solar radiation, fuel cell temperatures and load circumstances. The grid and PV side irregularities are handled by the hybrid energy system of PV and fuel cell. The proposed system is tested by simulate in the MATLAB/Simulink platform to analyse its performance.