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
@article{MaeRid:15-011,
author = {Maestre, Jos{\'{e}} M. and Ridao, Miguel A. and Kozma, Atilla and
Savorgnan, Carlo and Diehl, Moritz and Doan, Minh Dang and
Sadowska, Anna and Keviczky, Tam{\'a}s and De Schutter, Bart and
Scheu, Holger and Marquardt, Wolfgang and Valencia, Felipe and
Espinosa, Jairo},
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}
}