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

Skworcow, Piotr; Paluszczyszyn, Daniel; Ulanicki, Bogumił

doi:10.5194/dwes-7-53-2014

Cited by 20 publications

(7 citation statements)

References 14 publications

(14 reference statements)

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“…The implementation of valve control actions depends on valve construction. We refer interested readers to [15,36,31,1,37] for more details. The deployment of PRVs in water distribution networks can promote the potential control availability.…”

Section: Pressure Reduce Valvesmentioning

confidence: 99%

Optimal Pump Control for Water Distribution Networks via Data-based Distributional Robustness

Guo¹,

Wang²,

Taha³

et al. 2020

Preprint

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In this paper, we propose a data-based methodology to solve a multi-period stochastic optimal water flow (OWF) problem for water distribution networks (WDNs). The framework explicitly considers the pump schedule and water network head level with limited information of demand forecast errors for an extended period simulation. The objective is to determine the optimal feedback decisions of network-connected components, such as nominal pump schedules and tank head levels and reserve policies, which specify device reactions to forecast errors for accommodation of fluctuating water demand. Instead of assuming the uncertainties across the water network are generated by a prescribed certain distribution, we consider ambiguity sets of distributions centered at an empirical distribution, which is based directly on a finite training data set. We use a distance-based ambiguity set with the Wasserstein metric to quantify the distance between the real unknown data-generating distribution and the empirical distribution. This allows our multi-period OWF framework to trade off system performance and inherent sampling errors in the training dataset. Case studies on a three-tank water distribution network systematically illustrate the tradeoff between pump operational cost, risks of constraint violation, and out-of-sample performance.

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Section: Pressure Reduce Valvesmentioning

confidence: 99%

Optimal Pump Control for Water Distribution Networks via Data-based Distributional Robustness

Guo¹,

Wang²,

Taha³

et al. 2020

Preprint

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“…Note that the head loss H i,j [k] is a non-negative variable. For more information on valves, we refer the reader to [27]- [28]. 6) Pipes: When a pipe (i, j) ∈ L carries a non-zero water flow, energy must be conserved between the two junctions i and j; otherwise, the pressure heads at junctions i and j are decoupled.…”

Section: ) Pressure Reducing Valvesmentioning

confidence: 99%

“…Recent demonstrations of PRVs have shown their benefits in control capabilities [27]- [28], and have incentivized water network operators to invest in PRVs. In the near future, we envision PRVs will be available at all junctions with multiple incoming-outgoing pipes.…”

Section: Discretization and Approximationmentioning

confidence: 99%

Utilization of Water Supply Networks for Harvesting Renewable Energy

Fooladivanda

Domínguez-García

Sauer

2019

IEEE Trans. Control Netw. Syst.

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Renewable surplus power is increasing due to the increasing penetration of these intermittent resources. In practice, electric grid operators either curtail the surplus energy resulting from renewable-based generations or utilize energy storage resources to absorb it. In this paper, we propose a framework for utilizing water pumps and tanks in water supply networks to absorb the surplus electrical energy resulting from renewablebased electricity generation resources in the electrical grid. We model water supply networks analytically, and propose a twostep procedure that utilizes the water tanks in the water supply network to harvest the surplus energy from an electrical grid. In each step, the water network operator needs to solve an optimization problem that is non-convex. To compute optimal pump schedules and water flows, we develop a second-order cone relaxation and an approximation technique that enable us to transform the proposed problems into mixed-integer secondorder cone programs. We then provide the conditions under which the proposed relaxation is exact, and present an algorithm for constructing an exact solution to the original problem from a solution to the relaxed problem. We demonstrate the effectiveness of the proposed framework via numerical simulations.Index Terms-Water-energy nexus, energy harvesting, optimal water flow, water networks, second-order cone relaxation. arXiv:1808.05046v1 [cs.SY] 15 Aug 2018Recent demonstrations of PRVs have shown their benefits in control capabilities [27]-[28], and have incentivized water network operators to invest in PRVs. In the near future, we envision PRVs will be available at all junctions with multiple incoming-outgoing pipes. When the network topology does not

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“…Control of network elements such as valves and pumps, for optimal pressure, leakage and pipe damage reduction and energy cost minimization has been the focus of numerous works in the literature (for example Wright et al (2015); León-Celi et al (2018); Fooladivanda & Taylor (2018); Skworcow et al (2014); Ghaddar et al (2015Ghaddar et al ( , 2017). Furthermore, the use of variable speed pumps (instead of fixed speed) offers greater control and adaptability within a water distribution network, which can increase energy savings and reduce maintenance costs (Page et al, 2017).…”

Section: Introductionmentioning

confidence: 99%