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

Autores

VELARDE RUEDA, PABLO ANIBAL, Valverde, L. , Maestre, J. M. , Ocampo-Martinez, C. , Bordons, C.

Publicación externa

Si

Medio

J Power Sources

Alcance

Article

Naturaleza

Científica

Cuartil JCR

Cuartil SJR

Impacto JCR

6.945

Impacto SJR

2.202

Fecha de publicacion

01/03/2017

ISI

000395211200021

Scopus Id

2-s2.0-85009877493

Abstract

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. (C) 2017 Elsevier B.V. All rights reserved.

Palabras clave

Hydrogen storage; Microgrid; Model predictive control; Stochastic processes; Supply; Demand

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