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

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Authors

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.