Potential of model predictive control of a polder water system including pumps, weirs and gates

K. Horváth (Corresponding author), B. van Esch (Corresponding author), T. Vreeken, T. Piovesan, J. Talsma, I. Pothof

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

This work presents an assessment of the potential of model predictive control (MPC) of a Dutch polder system. The system drains to the Linge river and includes 13 weirs, 4 hydraulic gates and 4 large pumping stations each equipped with multiple pumps, managed by the Water Board Rivierenland. The management of the system must comply with several goals: keep the water levels within the bounds of safety, pump out the excess water at minimum cost or CO2 emission, but always have enough water for irrigation and shipping. To achieve these goals there are weirs regulating the water level in different pools, pumping stations to pump water in and out and gates to let water in and out by free flow when possible. These pumping stations consume large amounts of energy. We propose multi-objective mixed-integer optimization by using goal programming to prioritize different operational objectives. For the control of the pumps mixed-integer optimization is used, which makes it possible to not only model the energy consumption of the pumps while in operation, but also to model if the pumps are turned on or off. The control system is implemented using RTC-Tools, an open-source software tool to implement MPC. It is demonstrated that the proposed control system implementation can comply with the operational goals of the water board: keeping the water levels within the bounds while reducing the operational costs. The proposed control system has been tested numerically on data from the year 2013, and it is shown that it highly outperforms the current operation.

Original languageEnglish
Pages (from-to)128-140
Number of pages13
JournalJournal of Process Control
Volume119
DOIs
Publication statusPublished - Nov 2022

Funding

The authors thank Water Board Rivierenland for sharing their data. This research is carried out within the Slim Malen project. The Slim Malen (Smart Drainage) project is funded and performed by the following partners: STOWA, The Netherlands , Ministry of Economic Affairs, The Netherlands (RVO), Deltares, The Netherlands , Eindhoven University of Technology, The Netherlands , Ministry of Infra and Environment (Rijkswaterstaat – WVL), The Netherlands , Water Boards Hoogheemraadschap Hollands Noorderkwartier, The Netherlands , Fryslân, The Netherlands , Zuiderzeeland, The Netherlands , Rivierenland, The Netherlands , Scheldestromen, The Netherlands , Rijnland, The Netherlands , Brabantse Delta and Hollandse Delta, The Netherlands , and by companies Nelen & Schuurmans, The Netherlands , e-Risk Group, The Netherlands , Eneco, The Netherlands , Delta, The Netherlands , Alliander EXE, The Netherlands , Actility, The Netherlands , XYLEM, The Netherlands , and KISTERS, The Netherlands .

FundersFunder number
Eindhoven University of Technology
Ministerie van Economische Zaken en Klimaat

    Keywords

    • Automatic
    • Canal
    • Convex optimization
    • Model
    • Model predictive control
    • Pumps
    • Water

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