A comparison of distributed MPC schemes on a hydro-power plant benchmark


Reference:

J.M. Maestre, M.A. Ridao, A. Kozma, C. Savorgnan, M. Diehl, M.D. Doan, A. Sadowska, T. Keviczky, B. De Schutter, H. Scheu, W. Marquardt, F. Valencia, and J. Espinosa, "A comparison of distributed MPC schemes on a hydro-power plant benchmark," Optimal Control Applications and Methods, vol. 36, no. 3, pp. 306-332, May-June 2015.

Abstract:

In this paper we analyze and compare five distributed model predictive control (DMPC) schemes using a hydro-power plant benchmark. Besides being one of the most important sources of renewable power, hydro power plants present very interesting control challenges. The operation of a hydro-power valley involves the coordination of several subsystems over a large geographical area in order to produce the demanded energy while satisfying constraints on water levels and flows. In particular, we test the different DMPC algorithms using a 24 hour power tracking scenario in which the hydro-power plant is simulated with an accurate non-linear model. In this way, it is possible to provide a qualitative and quantitative comparison between different DMPC schemes implemented on a common benchmark, which is a type of assessment rare in the literature.

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Bibtex entry:

@article{MaeRid:15-011,
author={J.M. Maestre and M.A. Ridao and A. Kozma and C. Savorgnan and M. Diehl and M.D. Doan and A. Sadowska and T. Keviczky and B. {D}e Schutter and H. Scheu and W. Marquardt and F. Valencia and J. Espinosa},
title={A comparison of distributed {MPC} schemes on a hydro-power plant benchmark},
journal={Optimal Control Applications and Methods},
volume={36},
number={3},
pages={306--332},
month=may # {--} # jun,
year={2015},
doi={10.1002/oca.2154}
}


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