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Updated: Apr 15, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Published on: December 9, 2012

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A generic methodology for the optimisation of sewer systems using stochastic programming and self-optimizing control.

Miguel Mauricio-Iglesias1, Ignacio Montero-Castro1, Ane L Mollerup2

  • 1CAPEC-PROCESS, Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 229, Søltofts Plads, 2800 Lyngby, Denmark.

Journal of Environmental Management
|April 5, 2015
PubMed
Summary

This study introduces a new self-optimizing controller for sewer systems to minimize overflows. The innovative approach uses a two-stage optimization to manage current and future rainfall impacts effectively.

Keywords:
Combined sewers overflowControl designOptimisationSelf-optimising controlSewer systems

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Area of Science:

  • Environmental Engineering
  • Water Resource Management
  • Control Systems

Background:

  • Sewer system control is challenging due to network size, flow dynamics, and rainfall variability.
  • Existing control strategies often struggle to adapt to stochastic rainfall events and optimize performance.
  • Minimizing sewer overflows is crucial for environmental protection and public health.

Purpose of the Study:

  • To present a generic methodology for designing a self-optimizing controller for sewer systems.
  • To develop a control strategy that maintains near-optimal system performance by selecting optimal controlled variables.
  • To define an optimal performance metric that accounts for both immediate and probabilistic future overflows.

Main Methods:

  • A two-stage optimization process (stochastic and deterministic) was employed to define optimal performance.
  • The methodology involves selecting controlled variables to keep the sewer system near its optimal state.
  • The proposed controller was applied to a subcatchment area in Copenhagen for validation.

Main Results:

  • The developed self-optimizing controller demonstrated promising performance in a real-world sewer network.
  • The control strategy effectively managed overflows by considering both current and predicted rainfall.
  • The application in Copenhagen showed the methodology's practical applicability and potential.

Conclusions:

  • The proposed generic methodology offers a robust approach to designing self-optimizing controllers for sewer systems.
  • This advancement contributes to improving the operation and control of complex urban drainage infrastructure.
  • The findings are expected to advance the field of sewer system management and reduce environmental impact.