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Efficient Control of DC Microgrid with Hybrid PV— Fuel Cell and Energy Storage Systems (CROSBI ID 295198)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Subramanian ; Vasantharaj ; Vairavasundaram, Indragandhi ; Vairavasundaram, Subramaniyaswamy ; Yuvaraja, Teekaraman ; Ramya, Kuppusamy ; Nikolovski, Srete Efficient Control of DC Microgrid with Hybrid PV— Fuel Cell and Energy Storage Systems // Energies (Basel), 14 (2021), 11; 3234, 18. doi: https://www.mdpi.com/1996-1073/14/11/3234

Podaci o odgovornosti

Subramanian ; Vasantharaj ; Vairavasundaram, Indragandhi ; Vairavasundaram, Subramaniyaswamy ; Yuvaraja, Teekaraman ; Ramya, Kuppusamy ; Nikolovski, Srete

engleski

Efficient Control of DC Microgrid with Hybrid PV— Fuel Cell and Energy Storage Systems

Direct current microgrids are attaining attractiveness due to their simpler configuration and high-energy efficiency. Power transmission losses are also reduced since distributed energy resources(DERs) are located near the load. DERs such as solar panels and fuel cells produce the DC supply ; hence, the system is more stable and reliable. DC microgrid has a higher power efficiency than ACmicrogrid. Energy storage systems that are easier to integrate may provide additional benefits. In this paper, the DC micro-grid consists of solar photovoltaic and fuel cell for power generation, proposes a hybrid energy storage system that includes a super capacitor and lithium–ion battery for the battery improvement of power capability in the energy storage system. The main objective of this research work has been done for the enhanced settling point and voltage stability with the help of different maximum power point tracking (MPPT) methods. Different control techniques such as fuzzy logic controller, neural network, and particle swarm optimization are used to evaluate PV and FC through DC–DC boost converters for this enhanced settling point. When the test results are perceived, it is evidently attained that the fuzzy MPPT method provides an increase in the tracking capability of maximum power point and at the same time reduces steady-state oscillations. In addition, the time to capture the maximum power point is 0.035 s. It is about nearly two times faster than neural network controllers and eighteen times faster than for PSO, and it has also been discovered that the prefer red approach is faster compared to other control methods.

MPPT ; fuzzy logic controller (FLC) ; solar photovoltaic (PV) ; fuel cell (FC) ; DC-link ; artificial neural network (ANN) ; particle swarm optimization (PSO) (PDF) Efficient Control of DC Microgrid with Hybrid PV-Fuel Cell and Energy Storage Systems. Available from: https://www.researchgate.net/publication/352005789_Efficient_Control_of_DC_Microgrid_with_Hybrid_PV-Fuel_Cell_and_Energy_Storage_Systems#fullTextFileContent [accessed Jun 01 2021].

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Podaci o izdanju

14 (11)

2021.

3234

18

objavljeno

1996-1073

https://www.mdpi.com/1996-1073/14/11/3234

Trošak objave rada u otvorenom pristupu

Povezanost rada

Elektrotehnika

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