Title On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid
Authors VELARDE RUEDA, PABLO ANIBAL, Valverde, L. , Maestre, J. M. , Ocampo-Martinez, C. , Bordons, C.
External publication Si
Means J. Power Sources
Scope Article
Nature Científica
JCR Quartile 1
SJR Quartile 1
JCR Impact 6.94500
SJR Impact 2.20200
Publication date 01/03/2017
ISI 000395211200021
DOI 10.1016/j.jpowsour.2017.01.015
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.
Keywords Hydrogen storage; Microgrid; Model predictive control; Stochastic processes; Supply; Demand
Universidad Loyola members

Change your preferences Manage cookies