Neural Optimal Control Algorithm for Real Time Regulation of In-System Storage in Combined Sewer Systems

Darsono, Suseno; Labadie, John W.

doi:10.1061/40685(2003)226

Cited by 3 publications

(5 citation statements)

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“…It should be stressed that offline real time control still makes use of the information about current states of the integrated system in the actual control process. Surrogate models such as neural networks have been used to simulate each component of the integrated system, for example, sewer systems (Darsono and Labadie, 2007), wastewater treatment plant (Ráduly et al, 2007) or the integrated system itself, and this provides an effective way to improve computational efficiency for real time control optimization, particularly when these surrogate models are incorporated into genetic algorithms in the optimization process.…”

Section: Resultsmentioning

confidence: 99%

Multiple objective optimal control of integrated urban wastewater systems

Butler

Khu

2008

Environmental Modelling & Software

138

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Section: Resultsmentioning

confidence: 99%

Multiple objective optimal control of integrated urban wastewater systems

Butler

Khu

2008

Environmental Modelling & Software

138

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“…Most of the previous approaches in the literature utilised control measures for combined sewer overflows based on the volume of wastewater discharged from the sewer system without considering water quality (Beraud et al 2010, Cembrano et al 2004, Darsono et al 2007, Joseph-Duran et al 2014. However, Lau et al (2002) showed that, in isolation, the frequency and volume of discharges cannot be considered as accurate indicators of the receiving water quality because the biochemical oxygen demand, ammonia and dissolved oxygen concentrations lacked a strong relationship with the frequency and volume of discharges.…”

Section: Introductionmentioning

confidence: 99%

“…Also, while the effects of combined sewer discharges on the receiving water have been considered previously (Fu et al 2010, Lacour and Schutze 2010, Petruck et al 1998, Vanrolleghem et al 2005, Weinreich et al 1997 the associated trade-offs were not addressed directly. For example, the wastewater treatment costs corresponding to alternative control settings were not considered (Darsono andLabade 2007, Fu et al 2010). A major disadvantage of single-objective optimization (Cembrano et al 2004, Darsono et al 2007, Rauch et al 1999b is that it provides only one optimal solution to the problem.…”

Section: Introductionmentioning

confidence: 99%

“…For example, the wastewater treatment costs corresponding to alternative control settings were not considered (Darsono andLabade 2007, Fu et al 2010). A major disadvantage of single-objective optimization (Cembrano et al 2004, Darsono et al 2007, Rauch et al 1999b is that it provides only one optimal solution to the problem. Single objective optimization methods can be useful if the trade-off between the objectives is not important.…”

Section: Introductionmentioning

confidence: 99%

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Evolutionary Multi-Objective Optimal Control of Combined Sewer Overflows

Rathnayake

Tanyimboh

2015

Water Resour Manage

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This paper presents a novel multi-objective evolutionary optimization approach for the active control of intermittent unsatisfactory discharges from combined sewer systems. The procedure proposed considers the unsteady flows and water quality in the sewers together with the wastewater treatment costs. The distinction between the portion of wastewater that receives full secondary treatment and the overall capacity of the wastewater treatment works (including storm overflow tanks) is addressed. Temporal and spatial variations in the concentrations of the primary contaminants are incorporated also. The formulation is different from previous approaches in the literature in that in addition to the wastewater treatment cost we consider at once the relative polluting effects of the various primary contaminants in wastewater. This is achieved by incorporating a measure of the overall pollution called the effluent quality index. The differences between two diametrically opposed control objectives are illustrated, i.e. the minimization of the pollution of the receiving water or, alternatively, the minimization of the wastewater treatment cost. Results are included for a realistic interceptor sewer system that show that the combination of a multi-objective genetic algorithm and a stormwater management model is effective. The genetic algorithm achieved consistently the frontier optimal control settings that, in turn, revealed the trade-offs between the wastewater treatment cost and pollution of the receiving water.

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“…In 2005, a global optimal control system was applied to the Quebec westerly sewer network to minimize set-point variations in real-time and the frequency and volume of sewer overflows discharged into the basin's rivers [5]. Darsono and Labadie (2007) developed an RTC approach based on a neural-optimal algorithm to regulate in-line storages in combined sewer systems [6]. In the combined sewer system of Dresden city, Germany, a global RTC approach was implemented with a hydrodynamic pollution loadcalculation module to improve the efficiency of the sewer system [7].…”

Section: Introductionmentioning

confidence: 99%

A Real-Time Optimal Gate Operation Model for Urban Drainage Systems

Jafari¹,

Mousavi²,

Kim³

EPiC Series in Engineering

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Flooding is a phenomenon that endangers human being life and property. There are many structural and non-structural options that can be considered in order to reduce destructive effects of flooding. In this study, we propose a new methodology to enhance the performance of a real-time optimal operation model for flood mitigation in urban drainage systems. An online real-time model is developed as a simulation-optimization approach that leads to optimal operational policies based on the real-time rainfall information. Rainfall-runoff processes and hydraulic routing in the pipes are simulated by the EPA stormwater management model (SWMM) which is linked to the particle swarm optimization (PSO) algorithm, evaluating the system operation performance for assorted sets of operating policies. The initial solution in the real-time model is obtained by a long-term optimal operation model based on historical past flood events. The approach is validated by applying it to a portion of the urban drainage system in Tehran, the capital of Iran, consisting of a prototype network of pipes and detention reservoir equipped with controllable gates. Results show that the proposed strategy in introducing a reasonable initial solution to the real-time model can successfully enhance the performance of the model.

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Neural Optimal Control Algorithm for Real Time Regulation of In-System Storage in Combined Sewer Systems

Cited by 3 publications

References 0 publications

Multiple objective optimal control of integrated urban wastewater systems

Multiple objective optimal control of integrated urban wastewater systems

Evolutionary Multi-Objective Optimal Control of Combined Sewer Overflows

A Real-Time Optimal Gate Operation Model for Urban Drainage Systems

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