Wastewater Network Design: How Dynamic Network Management Software Changes the Standard Approach

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Wastewater Network Design: How Dynamic Network Management Software Changes the Standard Approach

A real-world study examining how WWTP design engineers have more flexibility when the network operator uses a real-time, predictive, optimization software.

More Flexibility in Wastewater Network Design: How Dynamic Network Management Software Changes the Standard Approach

Written by  Don Martin

The benefits of a fully autonomous, real-time control software used to optimize flow in mixed sewer networks – with the primary benefit being a reduction in combined sewer overflow events – are well understood and accepted1,2,3. But what cost efficiencies could be gained if, during the design phase of a wastewater treatment plant, engineers incorporated the use of this type of optimization software into their overall performance planning? What cost savings could be realized by reducing basin size, pumping or pipe capacity requirements while still achieving the same performance levels imposed by regulatory standards?

A Real-World Study Using Proven Software Tools


In 2012 the research team of what would soon become RTC4Water developed and installed Luxembourg’s first fully autonomous, predictive sewer network optimization software for a large, rural wastewater treatment plant. This installation has provided both the company and the treatment plant operator with a wealth of information and has become a proven platform for effectively evaluating new ideas. Recently, Luxembourg’s national water agency, l’Administration de la Gestion de l’Eau or AGE, partnered with RTC4Water to assess how classically developed engineering plans might be improved if the sewer network utilized a real-time network optimization software – in this case RTC4Water’s Global Predictive Controller (or GPC). For simplicity, this article will refer to a sewer network that uses this type of software as one that is dynamically managed (DM). The goal of the AGE study was to determine if engineering companies could reduce certain costs – financial as well as ecological – while still meeting required engineering norms and standards. As the wastewater treatment plant mentioned above was about to undergo an expansion project, a tangible, real-world assessment could be rapidly developed to find answers to these questions.

 

The Scope and Scale of the Study


The AGE supplied RTC4Water with the engineering plans for the new construction project. The area under consideration consisted of five rural communities which had been divided into 20 catchment areas. The design plans called for five mixed rainwater/sewage overflow (CSO) basins which were connected to a network and which then terminated at an existing wastewater treatment plant (WWTP). Rain fall data was provided by the AGE and another planning office developed the pollution load calculations (using KOSIM) which were taken into account by the engineering office to develop the final “classical static management design”, or CSM proposal (which also incorporated the German DWA A128 norm for pollution loads). To begin the study, the research team first focused on CSO outflow rates and overflow frequencies. Some of the scenarios which were developed for this initial analysis were: an assessment of a dynamically managed network against the CSM network whereby the maximum outflow of the CSO basins was not adjusted, a dynamically managed network compared against the CSM network whereby an adjustment of the CSO outflow was made (increased) but no modifications made to the intake flow rate of the WWTP, and finally an assessment of a dynamically managed network against the CSM network whereby an adjustment of the CSO outflow was made (increased) and intake flow into the WWTP was increased for a limited period of time. The research team also explored the scenario of a dynamically managed network against the CSM network whereby an adjustment of the CSO outflow rate was made (increased), a different pollution load classification for one of the CSOs in the network was added, but again no modifications made to the intake flow rate to the WWTP.

 

Virtual Environments Allow for Rapid Analysis


Naturally, before beginning the assessment of a dynamically managed flow approach, it is necessary to first have a virtual model which reflects the characteristics and behavior of the proposed CSM network design. As RTC4Water’s GPC software interacts with SWMM in a very efficient way, this software tool was used to develop the initial simulation environment for the non-dynamically managed network. The GPC optimization (dynamic management) software works with SWMM by querying the variables recorded in the SWMM model at every stage of the simulation, calculates the best control set points for a specific point in time, and then send these results back to the SWMM software with the data then being used to set the parameters for the next stage of the SWMM simulation. To represent the virtual operations of the dynamically managed network design, a relatively simple model of the proposed network was developed within the GPC platform. In this way, a second virtual simulation environment was established which allowed different optimization scenarios to be explored at a very rapid rate. Inputs to SWMM-simulated rainwater catchment basins were used, which were then dynamically managed within the GPC virtual environment which would apply a fully autonomous, predictive flow control approach. At each step of the simulation (preformed every 10 minutes), the GPC stored not only the optimization results, but also the optimization problem to be solved and any network restrictions that might limit the final solution. Analysis of this data showed which changes to the network’s infrastructure design parameters (e.g. flow rates, basins sizes) would offer the greatest potential for improving overall network performance.

 

Results 


For illustration purposes, the research team have selected data from a week in February 2017 whereby the proposed non-dynamically managed - or CSM designed - network would have encountered medium sized overflow events. To keep this article short and concise, only a sampling of these results will be shown. If you are interested in a full description of the study parameters and the detailed results for each scenario, please contact RTC4Water and they will make the paper available to you.

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