Optimization-Based Selection of Hydrants and Valves Control in Water Distribution Networks for Fire Incidents Management

Nerantzis, Dimitrios; Stoianov, Ivan

doi:10.1109/jsyst.2022.3159764

Cited by 3 publications

(1 citation statement)

References 37 publications

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“…This is included as many large-scale WDN optimization studies have used IPOPT to compute locally optimal solutions for network controls (e.g. Pecci et al, 2019;Ulusoy et al, 2020;Nerantzis and Stoianov, 2022). Most of these studies, however, have applied a quadratic approximation (QA) to model the head loss function ψ(•) as the nonsmooth HW formula presents challenges for IPOPT, namely that its Hessian is unbounded at the origin.…”

Section: Multi-start Solvermentioning

confidence: 99%

Optimal design-for-control of self-cleaning water distribution networks using a convex multi-start algorithm

Jenks¹,

Pecci²,

Stoianov³

2022

Preprint

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The provision of self-cleaning velocities has been shown to reduce the risk of discolouration in water distribution networks (WDNs). Despite these findings, control implementations continue to be focused primarily on pressure and leakage management. This paper considers the control of diurnal flow velocities to maximize the self-cleaning capacity (SCC) of WDNs. We formulate a new optimal design-for-control problem where locations and operational settings of pressure control and automatic flushing valves are jointly optimized. The problem formulation includes a nonconvex objective function, nonconvex hydraulic conservation law constraints, and binary variables for modelling valve placement, resulting in a nonconvex mixed integer nonlinear programming (MINLP) optimization problem. Considering the challenges with solving nonconvex MINLP problems, we propose a heuristic algorithm which combines convex relaxations (with domain reduction), a randomization technique, and a multi-start strategy to compute feasible solutions. We evaluate the proposed algorithm on case study networks with varying size and degrees of complexity, including a large-scale operational network in the UK. The convex multi-start algorithm is shown to be a more robust solution method compared to an off-the-shelf genetic algorithm, finding good-quality feasible solutions to all design-for-control numerical experiments. Moreover, we demonstrate the implemented multi-start strategy to be a fast and scalable method for computing feasible solutions to the nonlinear SCC control problem. The proposed method extends the control capabilities and benefits of dynamically adaptive networks to improve water quality in WDNs.

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Section: Multi-start Solvermentioning

confidence: 99%