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International Journal of Hydrogen Energy
Article . 2024 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Adaptive DC-Voltage control based on Type-2 neuro-fuzzy controller in a hybrid stand-alone power network with hydrogen fuel cell and battery

Authors: Beşir Dandıl; Resul Coteli; Hakan Açıkgöz;

Adaptive DC-Voltage control based on Type-2 neuro-fuzzy controller in a hybrid stand-alone power network with hydrogen fuel cell and battery

Abstract

Today, hydrogen fuel cells (HFCs) have become very popular in various applications because of their ability to be a clean energy source. One of the difficulties associated with HFCs is their sluggish response to variations in the load. This paper presents a nested control strategy based on a type-2 neuro-fuzzy controller (T2NFC) to improve the HFC's dynamic response in a hybrid stand-alone power network using HFC and battery. A system model is constructed using Matlab-Simulink. An interleaved converter is used to draw the maximal power from the HFC and reduce the ripple in the HFC's current. Two T2NFCs control DC voltage and battery charge/discharge current. The robustness of the T2NFC is evaluated for input disturbance, output disturbance, and both disturbances. The results show that the proposed control strategy is robust against input and output disturbances. Also, it provides improved dynamic response of the HFC, lower ripple in HFC current, and less overshoot or undershoot in DC voltage both in transient and steady-state. For step reference input, the proposed controller improves settling time of 24.06 % and overshoot of 59.55 % compared to the conventional PI controller. The results verify the effectiveness of the proposed controller under different operating conditions of hybrid stand-alone power network with fuel cell and battery.

Country
Turkey
Keywords

Energy & Fuels, Battery, Nested control, Battery (Electrochemical Energy Engineering), Type-2 neuro-fuzzy controller, Hydrogen fuel cell, Interleaved converters, Hydrogen fuel cells, Electrochemistry, Stand -alone, Fuel cells, Interleaved converter, Supercapacitor, Power networks, Controllers, Power converters, Chemistry, Physical, Control strategies, Simulink, Secondary batteries, Maximum power point tracking algorithms, Fuzzy inference, Tracking (position), Dynamic response, Fuel Cell, Power quality, Maximum power point tracking algorithm, Electric network analysis, Electric loads, Neurofuzzy controllers, Hydrogen

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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