Run-time optimisation of sewer remote control systems using genetic algorithms and multi-criteria decision analysis: CSO and energy consumption reduction

Bonamente, E.; Termite, Loris Francesco; Garinei, Alberto; Menculini, Lorenzo; Marconi, Marcello; Piccioni, Emanuele; Biondi, Lorenzo; Rossi, Gianluca

doi:10.1080/10286608.2020.1771701

Cited by 5 publications

(4 citation statements)

References 29 publications

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“…Temporary change in the operational capacity of the system Pump capacity loss, data transmission loss was shown as promising for control (Bonamente et al 2020), although the conceptual UDS used has little basis in reality. Despite this new emphasis on GHG emissions in UDS control strategies, the specific focus on climate and social sustainability of RTC for UDS is still in its early stages (Ashagre et al 2020).…”

Section: Temporary Operational Changementioning

confidence: 99%

Towards the long term implementation of real time control of combined sewer systems: a review of performance and influencing factors

Werf

Kapelan

Langeveld

2022

Water Science and Technology

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Real Time Control (RTC) is widely accepted as a cost-effective way to operate urban drainage systems (UDS) effectively. However, what factors influence RTC efficacy and how this might change in the long term remains largely unknown. This paper reviews the literature to understand what these factors likely are, and how they can be assessed in the future. Despite decades of research, inconsistent definitions of the performance of RTC are used, hindering an objective and quantitative examination of the benefits and drawbacks of different control strategies with regard to their performance and robustness. Furthermore, a discussion on the changes occurring and projected to occur to UDS reveals that the potential impact of these changes on the functioning of RTC systems can be significant and should be considered in the design stage of the RTC strategy. Understanding this ‘best-before’ characteristic of an RTC strategy is the key step to ensure long term optimal functioning of the UDS. Additionally, unexplored potential for RTC systems might exist in the transitions, rehabilitation and construction of drainage systems. The research gaps highlighted here could guide the way for further development of RTC strategies, and enabling more optimal, long term implementation of RTC for urban drainage systems.

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Section: Temporary Operational Changementioning

confidence: 99%

Towards the long term implementation of real time control of combined sewer systems: a review of performance and influencing factors

Werf

Kapelan

Langeveld

2022

Water Science and Technology

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Section: Modelling-based Studiesmentioning

confidence: 99%

“…Genetic algorithm (GA) is an efficient algorithm/tool inspired by nature for real-time optimization of the sewer network system for effective decision making to control SO (Bonamente et al, 2020;Zimmer et al, 2015). GA has advantages of flexibility, prompt adaptation to changing conditions and reliability and limited CPU requirements (Bonamente et al, 2020). However, recent studies recommended combination of model predictive control and GA as well as GA and ANN for real-time control of urban sewer systems and to improve performance of GA and reduce network load without sacrificing quality (Petrosov et al, 2021;Rauch and Harremoes, 1999).…”

Section: Modelling-based Studiesmentioning

confidence: 99%

Impact of sewer overflow on public health: A comprehensive scientometric analysis and systematic review

Sojobi

Zayed

2022

Environmental Research

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“…Four of the 18 events were avoided, and the total CSO volume was reduced by 98.4% of the potential reducible volume. In addition, Bonamente et al (2020) demonstrated through a study conducted on a sewer system that a MPC based on the NSGA II optimization algorithm can save energy consumption up to 32% and an overflow of approximately 10%. Rathnayake & Faisal Anwar (2019) also successfully applied a MPC to the combined sewer network of Liverpool in the United Kingdom using the NSGA II and SWMM models.…”

Section: Introductionmentioning

confidence: 99%

Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems

Ghazouli

Khatabi

Soulhi³

et al. 2021

Water Science and Technology

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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.

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Run-time optimisation of sewer remote control systems using genetic algorithms and multi-criteria decision analysis: CSO and energy consumption reduction

Cited by 5 publications

References 29 publications

Towards the long term implementation of real time control of combined sewer systems: a review of performance and influencing factors

Towards the long term implementation of real time control of combined sewer systems: a review of performance and influencing factors

Impact of sewer overflow on public health: A comprehensive scientometric analysis and systematic review

Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems

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