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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