Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks

Chiang, Yi‐Ming; Chang, Li-Chiu; Tsai, Meng‐Che; Wang, Y.-F.; Chang, Fi‐John

doi:10.5194/hess-15-185-2011

Cited by 35 publications

(8 citation statements)

References 28 publications

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“…They use heuristic algorithms, based on externally imposed rules and previous knowledge of the drainage system (derived from experience and/or separate simulation procedures). The two most commonly used algorithms are Rule-Based Control (RBC) [51][52][53] and Fuzzy Logic Control (FLC) [54][55][56][57][58][59][60].…”

Section: Real-time Control Approachmentioning

confidence: 99%

On the Use of a Real-Time Control Approach for Urban Stormwater Management

Maiolo

Palermo

Brusco

et al. 2020

Water

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The real-time control (RTC) system is a valid and cost-effective solution for urban stormwater management. This paper aims to evaluate the beneficial effect on urban flooding risk mitigation produced by applying RTC techniques to an urban drainage network by considering different control configuration scenarios. To achieve the aim, a distributed real-time system, validated in previous studies, was considered. This approach uses a smart moveable gates system, controlled by software agents, managed by a swarm intelligence algorithm. By running the different scenarios by a customized version of the Storm Water Management Model (SWMM), the findings obtained show a redistribution of conduits filling degrees, exploiting the whole system storage capacity, with a significant reduction of node flooding and total flood volume.

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Section: Real-time Control Approachmentioning

confidence: 99%

On the Use of a Real-Time Control Approach for Urban Stormwater Management

Maiolo

Palermo

Brusco

et al. 2020

Water

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“…An FLC is also used to reduce the volume and number of overflows in the Wilhelmshaven (Germany) UDS achieving both objectives [15]. The principles of FLC have been used to control the operation of the pumps in the collection network od the city of Taipei, achieving a more efficient drainage of rainwater, and thus preventing flooding [16]. Another type of algorithm, the LQR regulator, has been applied in [17] to flow control in a collection network in Bavaria (Germany).…”

Section: Introductionmentioning

confidence: 99%

Distributed Model Predictive Control Applied to a Sewer System

2020

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In this work, a Distributed Model Predictive Control (MPC) methodology with fuzzy negotiation among subsystems has been developed and applied to a simulated sewer network. The wastewater treatment plant (WWTP) receiving this wastewater has also been considered in the methodology by means of an additional objective for the problem. In order to decompose the system into interconnected local subsystems, sectorization techniques have been applied based on structural analysis. In addition, a dynamic setpoint generation method has been added to improve system performance. The results obtained with the proposed methodology are compared to those obtained with standard centralized and decentralized model predictive controllers.

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“…An optimization algorithm has been widely used and applied to pump operation optimization. CFNN and ANFIS were proposed for extracting flood control knowledge and applied to the operation of a pumping station [21,22]. An online accurate model was constructed to forecast inundation levels during flood periods and used to optimize the operation of the pumping station [23].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Pump Start-Up Depth in Drainage Pumping Station Based on SWMM and PSO

Wang

Lei

Khu

et al. 2019

Water

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The pumps in multistage drainage pumping stations are often subject to frequent start-up and shutoffs during operation because of unreasonable start-up depths of the pumps; this will reduce the service lives of the pumps. To solve this problem, an optimization method for minimizing pump start-up and shutoff times is proposed. In this method, the operation of pumps in pumping station was optimized by constructing a mathematical optimization model. The storm water management model (SWMM) and particle swarm optimization (PSO) method were used to solve the problem and the optimal start-up depth of each pump is obtained. Nine pumping stations in Beijing were selected as a case study and this method was applied for multistage pumping station optimization and single pumping station optimization in the case study. Results from the case study demonstrate that the multistage pumping station optimization acquired a small number of pump start-up/shutoff times, which were from 8 to 114 in different rainfall scenarios. Compared with the multistage pumping station optimization, the single pumping station optimization had a bigger number of pump start-up/shutoff times, which were from 1 to 133 times, and the pump operating time was also longer, from 72 min to 7542 min. Therefore, the multistage pumping station optimization method was more suitable to reduce the frequency of pump start-up/shutoffs.

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Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks

Cited by 35 publications

References 28 publications

On the Use of a Real-Time Control Approach for Urban Stormwater Management

On the Use of a Real-Time Control Approach for Urban Stormwater Management

Distributed Model Predictive Control Applied to a Sewer System

Optimization of Pump Start-Up Depth in Drainage Pumping Station Based on SWMM and PSO

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