Low cost, high performance fuel cell energy conditioning system controlled by neural network

Received Apr 18, 2020 Revised Jun 17, 2020 Accepted Jul 9, 2020 Keywords: Boost converter Continuous conduction mode Energy conditioning system Fuel cell Neural network ABSTRACT Fuel cells are an important option for the generation of renewable, efficient and environmentally friendly electricity. Th...

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Bibliographic Details
Published in:Telkomnika 2020-12, Vol.18 (6), p.3116-3122
Main Authors: Martínez S., Fredy H., S., Fernando Martínez, Ariza, Holman Montiel
Format: Article
Language:English
Subjects:
Acids
Alternative energy
Chemical reactions
Conditioning
Converters
Electric currents
Electric power
Electricity distribution
Electrodes
Electrolytes
Fuel cells
Gases
Hydrogen
Natural gas
Neural networks
R&D
Research & development
Residential energy
Topology
Vehicles
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Summary:Received Apr 18, 2020 Revised Jun 17, 2020 Accepted Jul 9, 2020 Keywords: Boost converter Continuous conduction mode Energy conditioning system Fuel cell Neural network ABSTRACT Fuel cells are an important option for the generation of renewable, efficient and environmentally friendly electricity. There are also commercial systems for domestic use (the home energy station (HES), for example) that produce hydrogen from natural gas for electric power generation. An energy supply system based on fuel cells requires, in addition to the battery, other elements for the handling and conditioning of gases, liquids and the final electrical energy as shown in Figure 2, these elements are known as balance of plant (BOP) [14, 15]. According to these conditions, and considering the performance and cost of the system, the boost regulator is selected as the power topology.
ISSN:1693-6930
2302-9293
DOI:10.12928/telkomnika.v18i6.16426