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Optimal sensor placement method for wastewater treatment plants based on discrete multi-objective state transition

Wenting Li¹, Jie Han¹, Yonggang Li¹

¹School of Automation, Central South University, Changsha, 410 083, China.

Journal of Environmental Management

|February 1, 2022

Summary

This summary is machine-generated.

Optimizing sensor placement in wastewater treatment plants (WWTPs) improves data utilization for better process control. This study presents a novel model and algorithm to enhance system efficiency and reduce costs.

Keywords:

Discrete multi-objective state transition algorithm Evaluation strategy Municipal wastewater treatment Sensor placement Weighting factors

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Area of Science:

Environmental Engineering
Process Control
Optimization

Background:

Effective parameter monitoring is crucial for wastewater treatment plant (WWTP) stability and efficiency.
Ubiquitous sensor installation generates rich data, but improper placement hinders actionable insights for system optimization.
Optimizing sensor placement is necessary to maximize the value of collected process data.

Purpose of the Study:

To develop a weighted sensor placement optimization model considering cost, information richness, and reliability.
To address the sensor optimization problem as a nonlinear mathematical programming problem.
To identify Pareto optimal solutions for improved sensor placement strategies in WWTPs.

Main Methods:

A weighted sensor placement optimization model was established.
A discrete multi-objective state transition algorithm was proposed to find Pareto optimal solutions.
An evaluation strategy was designed for selecting the most suitable industrial application solution.

Main Results:

The proposed method demonstrated validity and superiority in simulation experiments on three different WWTPs.
Increased degree of variable observability and measurement redundancy was achieved.
Sensor costs were maintained at a low level.

Conclusions:

The developed model and algorithm effectively optimize sensor placement in WWTPs.
The approach enhances data utilization for improved process stability and efficiency.
This method offers a cost-effective solution for industrial sensor network design.