Hydrogen consumption prediction of a fuel cell based system with a hybrid intelligent approach

Juan Aurelio Montero-Sousa, Héctor Aláiz-Moretón, Héctor Quintián, Tomás González-Ayuso, Paulo Novais and José Luis Calvo-Rolle

Energy, 2020, vol. 205, issue C

Abstract: Energy storage is one of the challenges of the electric sector. There are several different technologies available for facing it, from the traditional ones to the most advanced. With the current trend, it is mandatory to develop new energy storage systems that allow optimal efficiency, something that does not happen with traditional ones. Another feature that new systems must meet is to envisage the behaviour of energy generation and consumption. With this aim, the present research deals the hydrogen consumption prediction of a fuel cell based system thanks a hybrid intelligent approach implementation. The work is based on a real testing plant. Two steps have been followed to create a hybrid model. First, the real dataset has been divided into groups whose elements have similar characteristics. The second step, carry out the regression using different techniques. Very satisfactory results have been achieved during the validation of the model.

Keywords: Energy storage; Energy management; Fuel cell; SVM; ANN; BHL (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:205:y:2020:i:c:s0360544220310938

DOI: 10.1016/j.energy.2020.117986

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