Step by step development of a real fuel cell system. Design, implementation, control and monitoring

Segura, F.; Andújar, José Manuel

doi:10.1016/j.ijhydene.2015.01.178

Cited by 25 publications

(21 citation statements)

References 18 publications

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“…The PEM fuel cell that is part of the microgrid (Figure 9a) is made up of a stack with 80 single planar cells in series, with an active surface of 0.0145 m 2 /cell [39]. Its nominal power is 3.4 kW e , but due to stack degradation the actual power is limited by the control system to 2 kW e .…”

Section: Pem Fuel Cell Modelmentioning

confidence: 99%

Hydrogen vs. Battery in the Long-term Operation. A Comparative Between Energy Management Strategies for Hybrid Renewable Microgrids

et al. 2020

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The growth of the world’s energy demand over recent decades in relation to energy intensity and demography is clear. At the same time, the use of renewable energy sources is pursued to address decarbonization targets, but the stochasticity of renewable energy systems produces an increasing need for management systems to supply such energy volume while guaranteeing, at the same time, the security and reliability of the microgrids. Locally distributed energy storage systems (ESS) may provide the capacity to temporarily decouple production and demand. In this sense, the most implemented ESS in local energy districts are small–medium-scale electrochemical batteries. However, hydrogen systems are viable for storing larger energy quantities thanks to its intrinsic high mass-energy density. To match generation, demand and storage, energy management systems (EMSs) become crucial. This paper compares two strategies for an energy management system based on hydrogen-priority vs. battery-priority for the operation of a hybrid renewable microgrid. The overall performance of the two mentioned strategies is compared in the long-term operation via a set of evaluation parameters defined by the unmet load, storage efficiency, operating hours and cumulative energy. The results show that the hydrogen-priority strategy allows the microgrid to be led towards island operation because it saves a higher amount of energy, while the battery-priority strategy reduces the energy efficiency in the storage round trip. The main contribution of this work lies in the demonstration that conventional EMS for microgrids’ operation based on battery-priority strategy should turn into hydrogen-priority to keep the reliability and independence of the microgrid in the long-term operation.

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Section: Pem Fuel Cell Modelmentioning

confidence: 99%

Hydrogen vs. Battery in the Long-term Operation. A Comparative Between Energy Management Strategies for Hybrid Renewable Microgrids

et al. 2020

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“…The oxidant and cooling subsystem were built based on the manufacturer's instructions [55]. The complete sequence to put into operation the individual devices that make up the stack, the oxidation and cooling subsystem, the electric subsystem, and the implementation of the balance of plant (BoP), whose schema is shown in Figure 2 and a real image of the laboratory in Figure 3, were thoroughly explained in [56]. To test the system an Amrel PLA5K-120-1200 programmable electronic load was used.…”

Section: Case Of Studymentioning

confidence: 99%

Fuel Cell Output Current Prediction with a Hybrid Intelligent System

et al. 2019

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A fuel cell is a complex system, which produces electricity through an electrochemical reaction. For the formal application of control strategies on a fuel cell, it is very important to have a precise dynamic model of it. In this paper, a dynamic model of a real hydrogen fuel cell is obtained to predict its response. The data used in this paper to obtain the model have been acquired from a real fuel cell subjected to different load patterns by means of a programmable electronic load. Using this data, a nonlinear model based on a hybrid intelligent system is obtained. This hybrid model uses artificial neural networks to predict the output current of the fuel cell in a very precise way. The use of a hybrid scheme improves the performance of neural networks reducing to half the mean squared error obtained for a global model of the fuel cell.

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“…Figure 2 shows the diagram of the Balance of Plant (BoP) system, where all the subsystems are represented. In Figure 3, the real laboratory equipment is shown [64]. To perform different tests, a programmable electronic load was used (Amrel PLA5K-120-1200, San Diego, CA, USA).…”

Section: Test Benchmentioning

confidence: 99%

Fuel Cell Hybrid Model for Predicting Hydrogen Inflow through Energy Demand

et al. 2019

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Hydrogen-based energy storage and generation is an increasingly used technology, especially in renewable systems because they are non-polluting devices. Fuel cells are complex nonlinear systems, so a good model is required to establish efficient control strategies. This paper presents a hybrid model to predict the variation of H2 flow of a hydrogen fuel cell. This model combining clusters’ techniques to get multiple Artificial Neural Networks models whose results are merged by Polynomial Regression algorithms to obtain a more accurate estimate. The model proposed in this article use the power generated by the fuel cell, the hydrogen inlet flow, and the desired power variation, to predict the necessary variation of the hydrogen flow that allows the stack to reach the desired working point. The proposed algorithm has been tested on a real proton exchange membrane fuel cell, and the results show a great precision of the model, so that it can be very useful to improve the efficiency of the fuel cell system.

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Step by step development of a real fuel cell system. Design, implementation, control and monitoring

Cited by 25 publications

References 18 publications

Hydrogen vs. Battery in the Long-term Operation. A Comparative Between Energy Management Strategies for Hybrid Renewable Microgrids

Hydrogen vs. Battery in the Long-term Operation. A Comparative Between Energy Management Strategies for Hybrid Renewable Microgrids

Fuel Cell Output Current Prediction with a Hybrid Intelligent System

Fuel Cell Hybrid Model for Predicting Hydrogen Inflow through Energy Demand

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