  In this work, an evaluation of Chance-Constrained Model Predictive Control
(CC-MPC) in sewer systems over the use of the classical deterministic Model
Predictive Control (MPC) is presented. The focus of this evaluation is on the
avoidance of weir overflow when uncertainty is present. Furthermore, the design
formulation of CC-MPC is presented with a comparison to the design of MPC. For
the evaluation, a simplified model of the Barcelona sewer network case study is
utilized. Our comparison shows that for sewer systems with uncertain inflows, a
CC-MPC allows for better statistical guarantees for avoiding weir overflow,
than relying on a deterministic MPC. A simple back-up strategy in case of
infeasible optimization program was also apparent for the CC-MPC based on the
results of the analysis.
