Model Predictive Control of Salinity and Water Level in a Hypothetical Polder Ditch: Is it Possible to Use the Discretized Linearized Physical Equations for Optimization

6 pages•Published: September 20, 2018

Abstract

Surface water salinization in deltaic areas due to saline groundwater exfiltration is an important issue. Fresh water diverted from the rivers is used for flushing the canals and the ditches in coastal areas to remove the low quality saline surface water mixed with saline groundwater. Worldwide, deltaic areas are under stress due to climate change, sea level increase and decrease in fresh water availability. The current fresh water management strategies in polders to overcome the salinization problem solely depends on uncontrolled freshwater use. However, this operation will not be effective during a scarce freshwater availability scenario and has to be revised for efficient management possibilities. With the advances in real time measurement of salinity and water level measurements, using a Model Predictive Control (MPC) scheme for the operation of a polder system is gaining popularity. MPC is a powerful control tool that can handle multiple objectives, consider the constraints and the uncertainties of the system. However, a MPC scheme requires a simple and reliable internal model that will be used to calculate the optimum control actions. The internal model should be robust, should reflect the system behaviour with enough detail and should not be computationally costly. In this paper, a MPC scheme is proposed using the discretized linearized De Saint Venant (SV) and Advection-Diffusion (AD) equations as the internal model of the controller. The proposed scheme will be able to control salinity and water level at any discretization point by manipulating the flushing and outflow discharges. This is an ongoing research with tests continuing on a realistic test case.

Keyphrases: flushing, Polders, Salinization, Water Quality Control, Water Quantity Control

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 117--122

Links:	https://easychair.org/publications/paper/4wvw
	https://doi.org/10.29007/rpmp