Better water quality and higher energy efficiency by using model predictive flow control at water supply systems

Bakker, M.; Vreeburg, J.H.G.; Palmen, Luc; Sperber, V.; Bakker, Geo; Rietveld, L.C.

doi:10.2166/aqua.2013.063

Cited by 42 publications

(24 citation statements)

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“…The DWF prediction is obtained by a measurement data driven technique (Bakker et al, 2013a). Based on real-time measured water levels in the sewerage and both rainfall and DWF predictions, a discharge limitation is determined by a volume optimisation technique (Bakker et al, 2013b).…”

Section: Methodsmentioning

confidence: 99%

“…This particular technique is based on the fully adaptive forecasting model for short-term drinking water demand (Bakker et al, 2013a). It is so generic that it can be applied to waste water discharge with some small adjustments of the settings.…”

Section: Dry-weather Flow Predictionmentioning

confidence: 99%

“…This technique is in principle equal to the predictive control applied in drinking water supply (Bakker et al, 2013b). For that specific purpose, the outflow of a reservoir is determined by the water demand prediction of the supply area, and the inflow of the reservoir is kept as constant as possible within the constraints.…”

Section: Predictive Controlmentioning

confidence: 99%

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Flow intake control using dry-weather forecast

Icke¹,

Schagen²,

Huising³

et al. 2017

Drink. Water Eng. Sci.

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Abstract.Level-based control of the influent flow causes peak discharges at a waste water treatment plant (WWTP) after rainfall events. Furthermore, the capacity of the post-treatment is in general smaller than the maximum hydraulic capacity of the WWTP. This results in a significant bypass of the post-treatment during peak discharge. The optimisation of influent flow reduces peak discharge, and increases the treatment efficiency of the whole water cycle, which benefits the surface water quality. In this paper, it is shown that half of the bypasses of the post-treatment can be prevented by predictive control. A predictive controller for influent flow is implemented using the Aquasuite ® Advanced Monitoring and Control platform. Based on real-time measured water levels in the sewerage and both rainfall and dry-weather flow (DWF) predictions, a discharge limitation is determined by a volume optimisation technique. For the analysed period (February-September 2016) results at WWTP Bennekom show that about 50 % of bypass volume can be prevented. Analysis of single rainfall events shows that the used approach is still conservative and that the bypass can be even further decreased by allowing discharge limitation during precipitation.

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Section: Methodsmentioning

confidence: 99%

Section: Dry-weather Flow Predictionmentioning

confidence: 99%

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Flow intake control using dry-weather forecast

Icke¹,

Schagen²,

Huising³

et al. 2017

Drink. Water Eng. Sci.

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“…Table 1 shows that model based control led to a 83% lower value for the production variation calculated with equation (1). Bakker et al (2013a) showed that treatment performance was better at lower values of production variation, resulting in lower values of the turbidity of the clear water. Pressure control Figure 6 and Figure 7 show trends of the water demand, the outlet pressure at the pumping station and the average pressure in the area of both examined periods.…”

Section: Figure 6: Difference Between Level Based (Upper Graph) and Mmentioning

confidence: 99%

“…Forecasting models are used by utilities around the world: In the Netherlands in 2012, 57% of all supplied water was controlled with predictive control models (Bakker et al, 2013a), leading to 5.2% lower energy costs and 19% lower turbidity of the clear water. Other examples of the implementation of predictive control are at four large utilities in the United States (Bunn and Reynolds, 2009), where a reduction of energy costs of 12% was achieved.…”

Section: Introductionmentioning

confidence: 99%

Advanced control of a water supply system: a case study

Bakker

Rajewicz²,

Kien

et al. 2014

Water Practice and Technology

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Conventional automatic production flow control and pump pressure control of water supply systems are robust and simple: production flow is controlled based on the level in the clear water reservoir and pump pressure is controlled on a static set-point. Recently, more advanced computerbased control methods were developed in which production flow is controlled by using a shortterm water demand forecasting model and pressure is controlled by a dynamic pressure control module. To assess the differences between conventional and advanced control, we examined operational data of water treatment plant (WTP) Gruszczyn that supplies drinking water to a part of the city of Poznań, Poland. We compared two periods of three weeks of conventional and advanced control. The comparison showed that with advanced control the variation in the production flow was 83% lower, and the pump pressure of the clear water pumps was 29% lower.The lower pressure resulted in 20% less background leakage and the overall system's energy costs were 11.5% lower.

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An adaptive ant colony optimization framework for scheduling environmental flow management alternatives under varied environmental water availability conditions

Szemis

Maier

Dandy

2014

Water Resources Research

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Human water use is increasing and, as such, water for the environment is limited and needs to be managed efficiently. One method for achieving this is the scheduling of environmental flow management alternatives (EFMAs) (e.g., releases, wetland regulators), with these schedules generally developed over a number of years. However, the availability of environmental water changes annually as a result of natural variability (e.g., drought, wet years). To incorporate this variation and schedule EFMAs in a operational setting, a previously formulated multiobjective optimization approach for EFMA schedule development used for long-term planning has been modified and incorporated into an adaptive framework. As part of this approach, optimal schedules are updated at regular intervals during the planning horizon based on environmental water allocation forecasts, which are obtained using artificial neural networks. In addition, the changes between current and updated schedules can be minimized to reduce any disruptions to longterm planning. The utility of the approach is assessed by applying it to an 89km section of the River Murray in South Australia. Results indicate that the approach is beneficial under a range of hydrological conditions and an improved ecological response is obtained in a operational setting compared with previous longterm approaches. Also, it successfully produces trade-offs between the number of disruptions to schedules and the ecological response, with results suggesting that ecological response increases with minimal alterations required to existing schedules. Overall, the results indicate that the information obtained using the proposed approach potentially aides managers in the efficient management of environmental water.

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Better water quality and higher energy efficiency by using model predictive flow control at water supply systems

Cited by 42 publications

References 0 publications

Flow intake control using dry-weather forecast

Flow intake control using dry-weather forecast

Advanced control of a water supply system: a case study

An adaptive ant colony optimization framework for scheduling environmental flow management alternatives under varied environmental water availability conditions

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