Proton Exchange Membrane Fuel Cell Modelling and Power Control by P&amp;O Algorithm

Naseri, Nisrine; Hani, Soumia El; Aghmadi, Ahmed; Harouri, Khadija El; Heyine, Mohamed Saleck; Mediouni, Hamza

doi:10.1109/irsec.2018.8703002

Cited by 17 publications

(13 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Naseri et al [6], Dharani [7], and Dargahi et al [8] introduced a perturb and observe (P&O) approach with a PEMFC to optimize the output power of the fuel cell. This MPPT algorithm compares the rate of change of power and current at each instant according to the step perturbation chosen to generate the maximum power output.…”

Section: Literature Reviewmentioning

confidence: 99%

Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System

Fam¹,

Wong

Basri

et al. 2021

IEEE Access

View full text Add to dashboard Cite

Section: Literature Reviewmentioning

confidence: 99%

Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System

Fam¹,

Wong

Basri

et al. 2021

IEEE Access

View full text Add to dashboard Cite

“…Basic, yet effective Perturb & Observe (P&O) algorithm is chosen for MPPT control [22]. Proton exchange membrane (PEM) fuel cell power module with nominal power capacity of 10kW is considered and details on modelling of fuel cell may be further referred in [23]. PEM fuel cell is connected to the common dc bus through dedicated dc-dc converter which enables the voltage matching of fuel cell with the dc bus voltage by performing dc-dc converter boost action [24].…”

Section: Figure 2 Proposed Energy Extraction Maximization Control Formentioning

confidence: 99%

Enhancing Energy Extraction for a Multi-Resource Standalone Microgrid

Tomar*

2020

IJITEE

View full text Add to dashboard Cite

In a microgrid configuration integrated with different types of distributed energy resources (DERs), dedicated DC-DC converter stage ensures matching of source characteristics, to avoid power losses occurred due to the mismatching phenomena. However, in absence of proper coordinated control between DC bus and the inverter control, this additional energy extracted at dc bus may not be fully utilized. In this paper, an energy extraction maximization (EEM) control concept is proposed to increase the extraction and transfer of energy from DC bus to the load side through inverter control mechanism. Microgrid with multiple PV sources, fuel cell, battery and supercapacitor as DERs is considered for demonstration and EEM control is implemented on centralized inverter keeping configuration of other distributed energy sources intact. To illustrate the performance of proposed control, MATLAB/Simulink simulation has been carried out. Results obtained shows that proposed EEM control ensures the increased extraction of energy from dc bus and further a hardware implementation of the proposed concept is required to reach on some concrete results.

show abstract

“…Samal et al [14] presented a comparative analysis of employing different types of interleaved boost converter used in MPPT with FC. Naseri et al [15] presented static and dynamic models for PEM fuel cell with P&O MPPT. Reddy et al [16] designed MPPT controller for PEM fuel cell using radial basis ANN, the presented FC system was used to supply powertrain with the aid of boost converter.…”

Section: Introductionmentioning

confidence: 99%

Recent Approach of Forensic-Based Investigation Algorithm for Optimizing Fractional Order PID-Based MPPT With Proton Exchange Membrane Fuel Cell

2021

View full text Add to dashboard Cite

The output power of the fuel cell (FC) is mainly depending on the membrane water content, temperature, the hydrogen and oxygen partial pressures. The polarization curve has one global maximum power to be tracked. Therefore, a robust maximum power point tracking (MPPT) is highly required to follow the optimal operating point under any operating conditions. In this article, a recent approach of forensic-based investigation (FBI) algorithm is proposed to identify the optimal parameters of fractional order PID-based MPPT with proton exchange membrane (PEM) fuel cell. FBI is selected due to its high accuracy and requirement of less computational efforts. The considered objective function to be minimized is the error between the voltage at maximum power (V MP ) and the actual one at FC terminals. To prove the robustness of the proposed methodology, four cases of operating conditions are analyzed which are constant membrane water content and temperature, constant membrane water content with variable temperature, variable membrane water content with constant temperature, and variable membrane water content with variable temperature. The obtained results are compared to other approaches such as incremental resistance (INCR), particle swarm optimizer (PSO), invasive weed optimizer (IWO), sin-cosine algorithm (SCA), and artificial ecosystem optimizer (AEO). In case (1), the proposed FBI-FOPID succeeded in achieving maximum power of 5185.101 W. While the minimum objective functions in the second, third, and fourth cases are 2.5736 V, 1.4436 V, and 1.1568 V respectively obtained via the proposed approach. The comparison confirmed the superiority of the proposed FBI-based MPPT compared with other methods.INDEX TERMS Fractional PID, MPPT, optimization, proton exchange membrane fuel cell.

show abstract

Proton Exchange Membrane Fuel Cell Modelling and Power Control by P&O Algorithm

Cited by 17 publications

References 3 publications

Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System

Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System

Enhancing Energy Extraction for a Multi-Resource Standalone Microgrid

Recent Approach of Forensic-Based Investigation Algorithm for Optimizing Fractional Order PID-Based MPPT With Proton Exchange Membrane Fuel Cell

Contact Info

Product

Resources

About