Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems
Urbanization and an increase in precipitation intensities due to climate change, in addition to limited urban drainage systems (UDS) capacity, are the main causes of combined sewer overflows (CSOs) that cause serious water pollution problems in many cities around the world. Model predictive control...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IWA Publishing
2022-01-01
|
| Series: | Water Science and Technology |
| Subjects: | |
| Online Access: | http://wst.iwaponline.com/content/85/1/398 |
| _version_ | 1798016358562136064 |
|---|---|
| author | Khalid El Ghazouli Jamal El Khatabi Aziz Soulhi Isam Shahrour |
| author_facet | Khalid El Ghazouli Jamal El Khatabi Aziz Soulhi Isam Shahrour |
| author_sort | Khalid El Ghazouli |
| collection | DOAJ |
| description | Urbanization and an increase in precipitation intensities due to climate change, in addition to limited urban drainage systems (UDS) capacity, are the main causes of combined sewer overflows (CSOs) that cause serious water pollution problems in many cities around the world. Model predictive control (MPC) systems offer a new approach to mitigate the impact of CSOs by generating optimal temporally and spatially varied dynamic control strategies of sewer system actuators. This paper presents a novel MPC based on neural networks for predicting flows, a stormwater management model (SWMM) for flow conveyance, and a genetic algorithm for optimizing the operation of sewer systems and defining the best control strategies. The proposed model was tested on the sewer system of the city of Casablanca in Morocco. The results have shown the efficiency of the developed MPC to reduce CSOs while considering short optimization time thanks to parallel computing. HIGHLIGHTS
Model predictive control of smart sewer networks.;
Artificial Neural Networks and parallel computing enhance the proactivity of the MPC.;
Real-Time Control.;
Combined sewer overflows reduction.; |
| first_indexed | 2024-04-11T15:49:23Z |
| format | Article |
| id | doaj.art-ab6cd45a71bb4bedb9bc04d14c98eb76 |
| institution | Directory Open Access Journal |
| issn | 0273-1223 1996-9732 |
| language | English |
| last_indexed | 2024-04-11T15:49:23Z |
| publishDate | 2022-01-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Water Science and Technology |
| spelling | doaj.art-ab6cd45a71bb4bedb9bc04d14c98eb762022-12-22T04:15:26ZengIWA PublishingWater Science and Technology0273-12231996-97322022-01-0185139840810.2166/wst.2021.511511Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systemsKhalid El Ghazouli0Jamal El Khatabi1Aziz Soulhi2Isam Shahrour3 Laboratoire de Génie Civil et géo-Environnement, Univ. Lille, IMT Lille Douai, Univ. Artois, Yncrea Hauts-de-France, ULR, 4515 - LGCgE, Lille F-59000, France Laboratoire de Génie Civil et géo-Environnement, Univ. Lille, IMT Lille Douai, Univ. Artois, Yncrea Hauts-de-France, ULR, 4515 - LGCgE, Lille F-59000, France National Higher School of Mines, Agdal Rabat, Morocco Laboratoire de Génie Civil et géo-Environnement, Univ. Lille, IMT Lille Douai, Univ. Artois, Yncrea Hauts-de-France, ULR, 4515 - LGCgE, Lille F-59000, France Urbanization and an increase in precipitation intensities due to climate change, in addition to limited urban drainage systems (UDS) capacity, are the main causes of combined sewer overflows (CSOs) that cause serious water pollution problems in many cities around the world. Model predictive control (MPC) systems offer a new approach to mitigate the impact of CSOs by generating optimal temporally and spatially varied dynamic control strategies of sewer system actuators. This paper presents a novel MPC based on neural networks for predicting flows, a stormwater management model (SWMM) for flow conveyance, and a genetic algorithm for optimizing the operation of sewer systems and defining the best control strategies. The proposed model was tested on the sewer system of the city of Casablanca in Morocco. The results have shown the efficiency of the developed MPC to reduce CSOs while considering short optimization time thanks to parallel computing. HIGHLIGHTS Model predictive control of smart sewer networks.; Artificial Neural Networks and parallel computing enhance the proactivity of the MPC.; Real-Time Control.; Combined sewer overflows reduction.;http://wst.iwaponline.com/content/85/1/398artificial intelligencecombined sewer overflowsgenetic algorithmmodel predictive controlreal-time controlsewer network |
| spellingShingle | Khalid El Ghazouli Jamal El Khatabi Aziz Soulhi Isam Shahrour Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems Water Science and Technology artificial intelligence combined sewer overflows genetic algorithm model predictive control real-time control sewer network |
| title | Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems |
| title_full | Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems |
| title_fullStr | Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems |
| title_full_unstemmed | Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems |
| title_short | Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems |
| title_sort | model predictive control based on artificial intelligence and epa swmm model to reduce csos impacts in sewer systems |
| topic | artificial intelligence combined sewer overflows genetic algorithm model predictive control real-time control sewer network |
| url | http://wst.iwaponline.com/content/85/1/398 |
| work_keys_str_mv | AT khalidelghazouli modelpredictivecontrolbasedonartificialintelligenceandepaswmmmodeltoreducecsosimpactsinsewersystems AT jamalelkhatabi modelpredictivecontrolbasedonartificialintelligenceandepaswmmmodeltoreducecsosimpactsinsewersystems AT azizsoulhi modelpredictivecontrolbasedonartificialintelligenceandepaswmmmodeltoreducecsosimpactsinsewersystems AT isamshahrour modelpredictivecontrolbasedonartificialintelligenceandepaswmmmodeltoreducecsosimpactsinsewersystems |