Chance-constrained stochastic MPC of Astlingen urban drainage benchmark network

Svensen, Jan Lorenz; Sun, Congcong; Cembraño, Gabriela; Puig, Vicenç

doi:10.1016/j.conengprac.2021.104900

Cited by 23 publications

(18 citation statements)

References 24 publications

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Section: Introductionmentioning

confidence: 99%

“…Furthermore, an increased number of actuators to optimize results in a larger search space, which increases the computational time further. To enable centralized MPC for larger UDS, (partial) linearization or oversimplification of the UDS dynamics are often used but can introduce significant uncertainties into the internal-MPC model, which can result in the loss of control performance potential (Van der Werf et al, 2023) or requires application of increasingly complex algorithms (e.g., Oh & Bartos, 2023;Svensen et al, 2021). As Naughton et al (2021) point out, the lack of clarity on the performance potential of real time optimization as well as the complexity of the procedures and algorithms and mistrust for oversimplified models are clear barriers for the widespread implementation of MPC strategies.…”

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confidence: 99%

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HAPPy to Control: A Heuristic And Predictive Policy to Control Large Urban Drainage Systems

Werf

Kapelan

Langeveld

2023

Water Resources Research

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Model Predictive Control (MPC) of Urban Drainage Systems (UDS) has been established as a cost‐effective method to reduce pollution. However, the operation of large UDS (containing over 20 actuators) can only be optimized by oversimplifying the UDS dynamics, potentially leading to a decrease in performance and reduction in users' trust, thus inhibiting widespread implementation of MPC procedures. A Heuristic And Predictive Policy (HAPPy) was set up, relying on the dynamic selection of the actuators with the highest impact on the UDS functioning and optimizing those in real‐time. The remaining actuators follow a pre‐set heuristic procedure. The HAPPy procedure was applied to two separate UDS in Rotterdam with the control objective being the minimization of overflow volume in each of the two cases. Results obtained show that the level of impact of the actuators on the UDS functioning changes during an event and can be predicted using a Random Forest algorithm. These predictions can be used to provide near‐global optimal actuator settings resulting in the performance of the HAPPy procedure that is comparable to a full‐MPC control and outperforming heuristic control procedures. The number of actuators selected to obtain near‐global optimal settings depends on the UDS and rainfall characteristics showing an asymptotic real‐time control (RTC) performance as the number of actuators increases. The HAPPy procedure showed different RTC dynamics for medium and large rainfall events, with the former showing a higher level of controllability than the latter. For medium events, a relatively small number of actuators suffices to achieve the potential performance improvement.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

HAPPy to Control: A Heuristic And Predictive Policy to Control Large Urban Drainage Systems

Werf

Kapelan

Langeveld

2023

Water Resources Research

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“…Steady‐state pressure of intake air flowrates was studied in the design of wastewater drainage networks 17 . Model predictive control was applied on the urban drainage system (UDS) to reduce the pollution of combined sewer overflow (CSO) and show the effects of the rainfall forecasting 18 . Partial differential equations are formulated on the flow dynamics in the pipelines of wastewater network and applied on urban drainage 19 .…”

Section: Introductionmentioning

confidence: 99%

“…17 Model predictive control was applied on the urban drainage system (UDS) to reduce the pollution of combined sewer overflow (CSO) and show the effects of the rainfall forecasting. 18 Partial differential equations are formulated on the flow dynamics in the pipelines of wastewater network and applied on urban drainage. 19 Empirical mode decomposition (EMD) and the long short-term memory (LSTM) model are proposed by Zhang et al to predict and improve the water quality in the urban drainage network.…”

mentioning

confidence: 99%

Management of physical and chemical water quality in Kotchener drain (Kafr El Sheikh, Egypt)

Osman,

Ali,

Bhran

et al. 2023

Asia-Pacific J Chem Eng

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Minimization of freshwater consumption is very important in the management of water quality in drainage systems. In this paper, a mathematical technique for mass integration in drain systems was proposed. The main objective of this work is to manage the water quality in Kotchener drain (El‐Gharbia main drain) by chasing the physical and chemical parameters at sources and sinks. Kotchener drain is one of the largest drains in the Nile delta which moves from south of Egypt to the Mediterranean Sea in the north direction. Firstly, the data were collected from the studied area for 2 years along the Kotchener drain area. This was achieved by monthly monitoring five parameters of six sources sites and five sinks' sites. The results reveal that the concentration of the sources parameters in catchment area are within the permissible limits, except major constituents of total dissolved solid (TDS), chemical oxygen demand (COD), and biological oxygen demand (BOD). According to the degree of pollutants in the Kotchener drain area, the effective parameters that affected the irrigation along the Nile delta were studied. Secondly, a mathematical model was constructed by input the data of sinks, sources, and discharge point to Mediterranean Sea. Distribution of wastewater and freshwater between sources and sinks were studied according to the limiting mass loads of sources and sinks. Furthermore, the variables were optimized by applying LINGO Software with adding assumptions and constrains. The most effective network with minimal negative environmental impact was obtained. Application of the introduced mathematical approach results in minimizing the freshwater consumption with minimizing the wastewater discharge.

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“…MPC is a well-studied control method [6,7], capable of dealing with prediction and constraints. It has successfully been applied to multiple fields, such as cement production [8], urban drainage [9], district heating [10], and more [11].…”

Section: Introductionmentioning

confidence: 99%

Peak Shaving in District Heating Utilizing Adaptive Predictive Control

Svensen

2022

Energies

Self Cite

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District heating systems (DHS) are driven by the heat demands of their consumers, with higher demands giving a higher load on the heat production. While heat demands are human-dependent, they contain diurnal behaviors and weather dependencies. The diurnal behaviors contain periods with high demands causing peak loads on the heat production, which is operationally costly. This is especially true for heat pumps, a solution for DHS to include green energy, as the cost depends directly on the needed temperature. This paper presents a formulation of adaptive model predictive control (MPC) for inducing peak shaving on the production load to handle the peak load problem by using the DHS distribution network as a heat storage. It also presents a simulator model to describe the DHS. The MPC was applied to data from a case study of the DHS in Brønderslev, Denmark, showing a peak reduction of around 8%.

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Chance-constrained stochastic MPC of Astlingen urban drainage benchmark network

Cited by 23 publications

References 24 publications

HAPPy to Control: A Heuristic And Predictive Policy to Control Large Urban Drainage Systems

HAPPy to Control: A Heuristic And Predictive Policy to Control Large Urban Drainage Systems

Management of physical and chemical water quality in Kotchener drain (Kafr El Sheikh, Egypt)

Peak Shaving in District Heating Utilizing Adaptive Predictive Control

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