Hydrogen energy storage integrated grid: A bibliometric analysis for sustainable energy production

Irham, Akmal; Roslan, M.F.; Jern, Ker Pin; Hannan, M.A.; Mahlia, T.M Indra

doi:10.1016/j.ijhydene.2024.03.235

Cited by 12 publications

(1 citation statement)

References 176 publications

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“…In this microgrid, P&O controls the battery state charging conditions as well as discharging state conditions. The working efficiency of the P&O method in this smart grid network is very low which is enhanced by using the Incremental Conductance (IC) technology 15 . This methodology provides more efficient power to the hydrogen vehicle system and gives a good dynamic system response.…”

Section: Introductionmentioning

confidence: 99%

Design of adaptive hybrid MPPT controllers with universal input voltage DC–DC converter for RES’s

Rafikiran,

Alsaif

2024

Sci Rep

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At present, conventional energy production is absent because of the more hazardous gases released into the environment, the high effect on human health, more cost required for maintenance, plus less usefulness for highly populated areas. So, the Renewable Energy Sources are more focused for the present automotive industry application. In this work, the Proton Exchange Membrane Fuel Stack is considered for analyzing the proposed DC–DC converter circuit. The advantages of this fuel stack are high energy density, fast functioning nature, more robustness, and more usefulness for the various water membrane conditions of the fuel stack. However, the disadvantages of the fuel stack are excessive current generation, plus more current conduction losses. So, the wide voltage supply single switch power converter is introduced in this work for optimizing the current production of the fuel stack network. The merits of this converter circuit are high stability, good reliability, low voltage appearing across the switches, plus a uniform power supply. Here, the converter switching pulses are obtained by proposing the Modified Continuous Step Change Adaptive Fuzzy Logic with Grey Wolf Optimization hybrid controller. This controller provides high maximum power extraction efficiency from the fuel stack which is equal to 99.421%. Also, this controller's Maximum Power Point Tracking time is 0.0285 s.

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Section: Introductionmentioning

confidence: 99%