Modeling, Diagnosis, and Control of Fuel-Cell-Based Technologies and Their Integration in Smart Grids and Automotive Systems

Kunusch, Cristian; Ocampo‐Martínez, Carlos; Valla, M.I.

doi:10.1109/tie.2015.2440212

Cited by 9 publications

(3 citation statements)

References 17 publications

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“…Renewable energy sources joined with hydrogen can be considered as efficient, clean, and sustainable energy source . In this sense, the laboratory‐scale plant was developed by HyLab for tests and experiments with various types of renewable energy and demands profiles.…”

Section: Description Of the Hydrogen‐based Microgridmentioning

confidence: 99%

Multicriteria optimal operation of a microgrid considering risk analysis, renewable resources, and model predictive control

Zafra-Cabeza

Velarde

Maestre

2019

Optim Control Appl Methods

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Summary This paper proposes an optimal power dispatch by taking into account risk management and renewable resources. In particular, it examines how control engineering and risk management techniques can be applied in the field of power systems through their use in the design of risk‐based model predictive controllers. To this end, this paper proposes a two‐layer control scheme for microgrid management where both levels are based on model predictive control (MPC): the higher level is devoted to risk management while the lower layer is dedicated to power dispatching. In particular, the high‐level controller is based on a risk‐based approach where potential risks have been identified and evaluated. Mitigation actions are the decision variables to be optimized to reduce the consequences of risks and costs. The MPC‐based algorithm decides the appropriate frequency of mitigation actions such as changes in references, constraints, and insurance contracting, by relying on a model that includes integer variables, identifiable risks, their costs, and the cost/benefit assessment of mitigating actions. On the other hand, the low‐level controller drives the plant to suitable values to satisfy demands. A series of simulations on a nonlinear model of a real laboratory‐scale power plant located in the facilities of the University of Seville are conducted under varying conditions to demonstrate the effectiveness of the algorithm when risks are explicitly considered.

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Section: Description Of the Hydrogen‐based Microgridmentioning

confidence: 99%

Multicriteria optimal operation of a microgrid considering risk analysis, renewable resources, and model predictive control

Zafra-Cabeza

Velarde

Maestre

2019

Optim Control Appl Methods

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“…Fuel cells (FCs) are effective energy conversion devices, used in various application branches-for instance, systems power auxiliaries, smart grids [1], automotive applications and transportation systems [2], and portable devices. Many FC technologies are available.…”

Section: Introductionmentioning

confidence: 99%

Improving the Performance of a Dual Kalman Filter for the Identification of PEM Fuel Cells in Impedance Spectroscopy Experiments

2019

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In this paper, the Dual Kalman Filter (DKF) is used for the parametric identification of an RC model of a Polymer Electrolyte Membrane Fuel Cell (FC) stack. The identification is performed for diagnostic purposes, starting from time-domain voltage and current signals in the framework of Electrochemical Impedance Spectroscopy (EIS) tests. Here, the sinusoidal input of the tests makes the identification of DKF parameters challenging. The paper analyzes the filter performance and proposes a possible approach to address the filter tuning to let it work with FC operating either in normal conditions or in the presence of drying and flooding fault conditions, or in fuel starvation mode. The analysis is mainly performed in a simulated environment, where the Fouquet model is used to simulate the FC. Some criteria to tune the filter are derived from the analysis and used also with experimental data produced by some EIS tests, to achieve the best estimate in constrained conditions. The results show that the DKF can be turned into a valuable tool to identify the model parameters even with signals developed for other scopes. The identification results envisage the possibility of assisting the model-based FC diagnosis by means of a very simple tool that can run on a low-cost embedded device. Indeed, the simplicity of the filter approach and a lightweight implementation allow the deployment of the algorithm in embedded solutions.

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“…In this work, we focus on the use of hydrogen as an energy vector for energy storage. Hydrogen, combined with other renewable energy sources, is a safe and viable option to mitigate the problems associated with hydrocarbon combustion because the entire system can be developed as an efficient, clean, and sustainable energy source, as mentioned in [3]. The hydrogen is converted into electrical energy by using fuel cells; the reverse process, i.e., the transformation of electric energy into hydrogen, is conducted by electrolysis [4], or ethanol reforming [5], among other techniques.…”

Section: Introductionmentioning

confidence: 99%

On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid

Velarde

Valverde

Maestre

et al. 2017

Journal of Power Sources

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In this paper, a performance comparison among three well-known stochastic model predictive control approaches, namely, multi-scenario, tree-based, and chance-constrained model predictive control is presented. To this end, three predictive controllers have been designed and implemented in a real renewable-hydrogen-based microgrid. The experimental set-up includes a PEM electrolyzer, lead-acid batteries, and a PEM fuel cell as main equipment. The real experimental results show significant differences from the plant components, mainly in terms of use of energy, for each implemented technique. Effectiveness, performance, advantages, and disadvantages of these techniques are extensively discussed and analyzed to give some valid criteria when selecting an appropriate stochastic predictive controller.

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Modeling, Diagnosis, and Control of Fuel-Cell-Based Technologies and Their Integration in Smart Grids and Automotive Systems

Cited by 9 publications

References 17 publications

Multicriteria optimal operation of a microgrid considering risk analysis, renewable resources, and model predictive control

Multicriteria optimal operation of a microgrid considering risk analysis, renewable resources, and model predictive control

Improving the Performance of a Dual Kalman Filter for the Identification of PEM Fuel Cells in Impedance Spectroscopy Experiments

On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid

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