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Main Authors: Wang, Ye, Weyer, Erik, Manzie, Chris, Simpson, Angus R., Blinco, Lisa
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2308.10466
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author Wang, Ye
Weyer, Erik
Manzie, Chris
Simpson, Angus R.
Blinco, Lisa
author_facet Wang, Ye
Weyer, Erik
Manzie, Chris
Simpson, Angus R.
Blinco, Lisa
contents Water distribution systems (WDSs) are typically designed with a conservative estimate of the ability of a control system to utilize the available infrastructure. The controller is designed and tuned after a WDS has been laid out, a methodology that may introduce unnecessary conservativeness in both system design and control, adversely impacting operational efficiency and increasing economic costs. To address these limitations, we introduce a method to simultaneously design infrastructure and develop control parameters, the co-design problem, with the aim of improving the overall efficiency of the system. Nevertheless, the co-design of a WDS is a challenging task given the presence of stochastic variables (e.g. water demands and electricity prices). In this paper, we propose a tractable stochastic co-design method to design the best tank size and optimal control parameters for WDS, where the expected operating costs are established based on Markov chain theory. We also give a theoretical result showing that the average long-run operating cost converges to the expected operating cost with probability~1. Furthermore, this method is not only applicable to greenfield projects for the co-design of WDSs but can also be utilized to improve the operations of existing WDSs in brownfield projects. The effectiveness and applicability of the co-design method are validated through three illustrative examples and a real-world case study in South Australia.
format Preprint
id arxiv_https___arxiv_org_abs_2308_10466
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Stochastic Co-design of Storage and Control for Water Distribution Systems
Wang, Ye
Weyer, Erik
Manzie, Chris
Simpson, Angus R.
Blinco, Lisa
Systems and Control
Water distribution systems (WDSs) are typically designed with a conservative estimate of the ability of a control system to utilize the available infrastructure. The controller is designed and tuned after a WDS has been laid out, a methodology that may introduce unnecessary conservativeness in both system design and control, adversely impacting operational efficiency and increasing economic costs. To address these limitations, we introduce a method to simultaneously design infrastructure and develop control parameters, the co-design problem, with the aim of improving the overall efficiency of the system. Nevertheless, the co-design of a WDS is a challenging task given the presence of stochastic variables (e.g. water demands and electricity prices). In this paper, we propose a tractable stochastic co-design method to design the best tank size and optimal control parameters for WDS, where the expected operating costs are established based on Markov chain theory. We also give a theoretical result showing that the average long-run operating cost converges to the expected operating cost with probability~1. Furthermore, this method is not only applicable to greenfield projects for the co-design of WDSs but can also be utilized to improve the operations of existing WDSs in brownfield projects. The effectiveness and applicability of the co-design method are validated through three illustrative examples and a real-world case study in South Australia.
title Stochastic Co-design of Storage and Control for Water Distribution Systems
topic Systems and Control
url https://arxiv.org/abs/2308.10466