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.