Abstract
The advanced control of urban drainage systems (UDS) has great potential in reducing pollution to the receiving waters by optimizing the operations of UDS infrastructural elements. Existing controls vary in complexity, including local and global strategies, Real-Time Control (RTC) and Model Predictive Control (MPC). Their results are, however, site-specific, hindering a direct comparison of their performance. Therefore, the working group ‘Integral Real-Time Control’ of the German Water Association (DWA) developed the Astlingen benchmark network, which has been implemented in conceptual hydrological models and applied to compare RTC strategies. However, the level of detail of such implementations is insufficient for testing more complex MPC strategies. In order to provide a benchmark for MPC, this paper presents: (1) The implementation of the conceptual Astlingen system in an open-source hydrodynamic model (EPA-SWMM), and (2) the application of an MPC strategy to the developed SWMM model. The MPC strategy was tested against traditional and well-established local and global RTC approaches, demonstrating how the proposed benchmark system can be used to test and compare complex control strategies.
Highlights
Real-time operations of urban drainage systems (UDS) have proven to be an efficient and cost-effective management strategy for reducing pollution to the aquatic environment without having to invest in expensive infrastructural expansions [1,2,3,4,5,6]
The simulated combined sewer overflows (CSO) volumes resulting from the application of Model Predictive Control (MPC) to the SWMM implementation of Astlingen are shown in Table 6, along with the percentage volume reduction compared to volumes for the base case (BC) and Equal-Filling Degree Verification (EFD) scenarios
The simulated number of CSO events and days with recorded CSOs for the MPC scenario are shown in Table 7, together with results from the BC and EFD scenarios
Summary
Real-time operations of urban drainage systems (UDS) have proven to be an efficient and cost-effective management strategy for reducing pollution to the aquatic environment without having to invest in expensive infrastructural expansions [1,2,3,4,5,6]. There is the need for a common method for comparing RTC and MPC approaches in order to support further advancements and widespread application of these technologies in both academia and practice [12]. Under this necessity, the working group ‘Integral Real-Time Control’ of the German Water Association (DWA). EPA-SWMM 5.1.013 [18] is a free, open-source software that is widely used in both academia and practice, thereby making the Astlingen benchmark case available to a wider audience. The MPC optimization was defined by the conceptual network of Astlingen, while the effects of the generated control setpoints were simulated in the SWMM model. To facilitate the wide usage of the results from this article for benchmarking, teaching, research and development, all the data, models, and codes used for the examples can be freely accessed on https://github.com/open-toolbox/SWMM-Astlingen
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