Dynamic Optimization Approach for Solving an Optimal Scheduling Problem in Water Distribution Systems

Ulanicki, Bogumił; Kahler, Jens; See, H.

doi:10.1061/(asce)0733-9496(2007)133:1(23)

Cited by 77 publications

(36 citation statements)

References 13 publications

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“…Note that such two-stages approach was reported in e.g. (Bounds et al, 2006;Ulanicki et al, 2007;Skworcow et al, 2009a). In this work the post-processing algorithm to generate an integer solution allows up to two on/off switches during a specified time interval (typically 1 to 3 hours).…”

Section: Methodsmentioning

confidence: 88%

“…The cost of electrical energy used for water treatment and pumping is a major factor contributing to the operational cost of WDS (Ulanicki et al, 2007). Typically operation of pump stations in WDS is governed by some local control loops; number of pumps switched on and their speed (if the pump station is equipped with variable speed drive) usually depends on levels of reservoirs.…”

Section: Problem Formulationmentioning

confidence: 99%

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Model Predictive Control for Energy and Leakage Management in Water Distribution Systems

Skworcow

Ulanicki

AbdelMeguid

et al. 2010

UKACC International Conference on CONTROL 2010

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This paper considers development of a methodology for an on-line energy and leakage management in water distribution systems, formulated within a model predictive control framework. The approach involves calculation of control actions, i.e. time schedules for pumps, valves and sources, to minimize the costs associated with energy used for water pumping and treatment and water losses due to leakage, whilst satisfying all operational constraints. The process of computing the control action utilises EPAnet hydraulic simulator, a mathematical modelling language called GAMS and a non-linear programming solver called CONOPT. The proposed control scheme has been integrated with an industrial SCADA system from ABB and interfaced with an actual medium-scale water distribution systems being part of Yorkshire Water Services. The scheme is currently being tested using on-line telemetry data. It has been operational for over 1 month with 1 hour sampling time and the preliminary results described in this paper indicate a potential for savings of 30% of the cost of electrical energy.

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Section: Methodsmentioning

confidence: 88%

Section: Problem Formulationmentioning

confidence: 99%

Model Predictive Control for Energy and Leakage Management in Water Distribution Systems

Skworcow

Ulanicki

AbdelMeguid

et al. 2010

UKACC International Conference on CONTROL 2010

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“…In most water distribution systems, the pumping of treated water from reservoirs to supply zones and storage tanks consumes most of the energy budget for a utility. For example, by a clever use of the storage tanks and reservoirs, pumping schedules can be shifted to cheap tariff periods resulting in significant savings [15,20]. Such pump scheduling are particularly challenging because the associated mathematical optimization problems combine integer variables (pump ON/OFF) with continuous nonlinear constraints of nodal pressures and pipe flows; these result in optimization problems of Mixed Integer Nonlinear Programming (MINLP) type.…”

Section: Design Overviewmentioning

confidence: 99%

“…Since the difficulty in solving MINLP problems scales prohibitively large with problem size, such approaches cannot be used in a near real time operational setting for large scale water networks. In [20] and references therein, the problem can be approximated by one that finds optimal reservoir trajectories. A much smaller global optimization method can then be solved for each pumping station to find efficient pumping schedules that give rise to the already computed optimal trajectories.…”

Section: Design Overviewmentioning

confidence: 99%

WaterBox

Kartakis

Abraham

McCann

2015

Proceedings of the 1st ACM International Workshop on Cyber-Physical Systems for Smart Water Networks

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Smart water distribution networks are a good example of a large scale Cyber-Physical System that requires monitoring for precise data analysis and network control. Due to the critical nature of water distribution, an extensive simulation of decision making and control algorithms are required before their deployment. Although some aspects of water network behaviour can be simulated in software such as hydraulic responses in valve changes, software simulators are unable to include dynamic events such as leakages or bursts in physical models. Furthermore, due to safety concerns, contemporary large-scale testbeds are limited to the monitoring processes or control methods with well established safety guarantees. Sophisticated algorithms for dynamic and optimal water network reconfiguration are not yet widespread. This paper presents a small-scale testbed, WaterBox, which allows the simulation of emerging/advanced monitoring and control algorithms in a fail-safe environment. The flexible hydraulic, hardware, and software infrastructure enables a substantial number of experiments. On-going experiments are related to in-node data processing and decision making, energy optimization, event-driven communication, and automatic control.

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“…Optimised pump control strategies can be based either on time schedules, see e.g. Ulanicki et al (2007), or on feedback rules calculated offline, see e.g. .…”

Section: Introductionmentioning

confidence: 99%

Pump schedules optimisation with pressure aspects in complex large-scale water distribution systems

Skworcow

Paluszczyszyn

Ulanicki

2014

Drink. Water Eng. Sci.

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Abstract. This paper considers optimisation of pump and valve schedules in complex large-scale water distribution networks (WDN), taking into account pressure aspects such as minimum service pressure and pressuredependent leakage. An optimisation model is automatically generated in the GAMS language from a hydraulic model in the EPANET format and from additional files describing operational constraints, electricity tariffs and pump station configurations. The paper describes in details how each hydraulic component is modelled. To reduce the size of the optimisation problem the full hydraulic model is simplified using module reduction algorithm, while retaining the nonlinear characteristics of the model. Subsequently, a nonlinear programming solver CONOPT is used to solve the optimisation model, which is in the form of Nonlinear Programming with Discontinuous Derivatives (DNLP). The results produced by CONOPT are processed further by heuristic algorithms to generate integer solution. The proposed approached was tested on a large-scale WDN model provided in the EPANET format. The considered WDN included complex structures and interactions between pump stations. Solving of several scenarios considering different horizons, time steps, operational constraints, demand levels and topological changes demonstrated ability of the approach to automatically generate and solve optimisation problems for a variety of requirements.

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Dynamic Optimization Approach for Solving an Optimal Scheduling Problem in Water Distribution Systems

Cited by 77 publications

References 13 publications

Model Predictive Control for Energy and Leakage Management in Water Distribution Systems

Model Predictive Control for Energy and Leakage Management in Water Distribution Systems

WaterBox

Pump schedules optimisation with pressure aspects in complex large-scale water distribution systems

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