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

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.

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.

 * Online version of the paper
 * Corresponding technical report: pdf file (530 KB)
      Note: More information on the pdf file format mentioned above can be found here.

Bibtex entry:

        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},
        month=may # {--} # jun,

Go to the publications overview page.

This page is maintained by Bart De Schutter. Last update: March 21, 2022.