Publication
On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid
Journal Article (2017)
Journal
Journal of Power Sources
Pages
161-173
Volume
343
Doc link
http://dx.doi.org/10.1016/j.jpowsour.2017.01.015
File
Authors
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Velarde, Pablo
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Valverde, Luis
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Maestre Torreblanca, José María
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Ocampo Martínez, Carlos A.
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Bordons, Carlos
Projects associated
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.
Categories
automation, control theory, optimisation.
Author keywords
Hydrogen storage, Microgrid, Model predictive control, Stochastic processes, Supply and demand
Scientific reference
P. Velarde, L. Valverde, J.M. Maestre, C. Ocampo-Martínez and C. Bordons. On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid. Journal of Power Sources, 343: 161-173, 2017.
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