Optimization of the proton exchange membrane fuel cell hybrid power system for residential buildings

Bizon, Nicu; Mazăre, Alin Gheorghita; Ionescu, Laurenţiu Mihai; Enescu, Florentina Magda

doi:10.1016/j.enconman.2018.02.025

Cited by 50 publications

(15 citation statements)

References 73 publications

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“…The diagram of the FCHPS Energy Management Unit (EMU) is presented in Figure 1. The setting block will select one of the RTO strategies proposed in the literature [17,29,38,44,[56][57][58][59] (see the right side of the Figure 1 and Table 1, where the references are mentioned in the last column) in order to evaluate the fuel economy under the same load profile. The performance under constant load could be measured by different indicators, such as the generated FC net power (P FCnet ) or the fuel consumption efficiency (Fuel e f f P FCnet / FuelFr), which are both important to be optimized.…”

Section: The Energy Management Unit Of the Fuel Cell Hybrid Power Systemmentioning

confidence: 99%

“…The interested reader can search the following references [17,29,38,44,[56][57][58][59]] for the hybrid system configuration, the control block diagrams, and the setting used for each strategy analyzed in this study.…”

Section: The Energy Management Unit Of the Fuel Cell Hybrid Power Systemmentioning

confidence: 99%

“…• Modeling, control, and optimization of the FC system to improve the fuel economy [10][11][12]; • Developing innovative solutions and advanced technologies to improve the lifetime, reliability and safety in operation of the FC system [13,14]; • Numerical models for the control of hydrogen and thermal/electric energies productions through Solid Oxide Electrolyzer/Fuel Cells [15]: • Proposal of innovative stand-alone or grid-connected RES HPS architectures, which can be optimized based on advanced Energy Management Strategies (EMSs) [16][17][18] and Global Maximum Power Point Tracking (GMPPT) control algorithms [19][20][21] applied to available RESs (photovoltaic systems, wind turbines etc.) in order to optimally ensure the power flow balance on the DC bus (and/or the AC bus) [22][23][24] and improve the harvested energy from the RESs [25][26][27]; • Hybridization of the RES HPS with an FC system as backup energy source (FC/RES HPS) to mitigate the RES power variability and load dynamics by controlling the generated FC power at the level of the required power on the DC bus [28][29][30].…”

Section: Introductionmentioning

confidence: 99%

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Optimization of the Fuel Cell Renewable Hybrid Power System Using the Control Mode of the Required Load Power on the DC Bus

2019

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In this paper, a systematic analysis of seven control topologies is performed, based on three possible control variables of the power generated by the Fuel Cell (FC) system: the reference input of the controller for the FC boost converter, and the two reference inputs used by the air regulator and the fuel regulator. The FC system will generate power based on the Required-Power-Following (RPF) control mode in order to ensure the load demand, operating as the main energy source in an FC hybrid power system. The FC system will operate as a backup energy source in an FC renewable Hybrid Power System (by ensuring the lack of power on the DC bus, which is given by the load power minus the renewable power). Thus, power requested from the batteries’ stack will be almost zero during operation of the FC hybrid power system based on RPF-control mode. If the FC hybrid power system operates with a variable load demand, then the lack or excess of power on the DC bus will be dynamically ensured by the hybrid battery/ultracapacitor energy storage system for a safe transition of the FC system under the RPF-control mode. The RPF-control mode will ensure a fair comparison of the seven control topologies based on the same optimization function to improve the fuel savings. The main objective of this paper is to compare the fuel economy obtained by using each strategy under different load cycles in order to identify which is the best strategy operating across entire loading or the best switching strategy using two strategies: one strategy for high load and the other on the rest of the load range. Based on the preliminary results, the fuel consumption using these best strategies can be reduced by more than 15%, compared to commercial strategies.

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Section: The Energy Management Unit Of the Fuel Cell Hybrid Power Systemmentioning

confidence: 99%

Section: The Energy Management Unit Of the Fuel Cell Hybrid Power Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimization of the Fuel Cell Renewable Hybrid Power System Using the Control Mode of the Required Load Power on the DC Bus

2019

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“…Also, it is implemented in microgrid applications . In addition, the PEMFC is used in several domestic applications …”

Section: Introductionmentioning

confidence: 99%

“…12 In addition, the PEMFC is used in several domestic applications. 13 Recently, several studies have been reported to model the PEMFCs which are collected and summarized by Karanfil in 2020. 14 Actually, the principal goal of these studies is to create a precise model of the PEMFC that can represent it accurately in simulation studies.…”

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confidence: 99%

Parameters extraction of PEMFC's model using manta rays foraging optimizer

2020

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Summary In this article, a recently developed bio‐inspired based manta rays foraging optimizer (MRFO) is attempted for reliable and accurate extraction of the model uncertain parameters of proton exchange membrane fuel cells (PEMFCs). The parameter estimation is formulated as a non‐linear optimization problem subject to set of restrictions. The great development and tremendous revolution of computation heuristic‐based algorithms are the impetus of the authors to apply the MRFO to solve this constrained optimization problem resulting in a precise PEMFC model. Three case studies of typical field PEMFC stacks namely Ballard type Mark V, NedStack type PS6, and Horizon type H‐12. Various I to V datasets are demonstrated to appraise the performance of MRFO among other recent optimizers available in the literature. To be objective and for sake of quantifications, the best scores of minimum fitness values are 0.8533, 2.1360, and 0.0966 for the later said PEMFC stacks, correspondingly. At a later stage, production of various characteristics under varying operating conditions such as changeable cell temperature and regulating pressures are established using the generated best values of PEMFCs model. Further calculations of statistical indices are performed to validate the robustness of obtained results by the MRFO. Through comprehensive performance assessments, it can be confirmed that MRFO is very promising tool for the effective extraction of PEMFCs' model and suggested to be applied for solving other engineering problems.

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