Stochastic Co-Design of Storage and Control for Water Distribution Systems
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 article, 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.
Authors
- Chris Manzie (ORCID: https://orcid.org/0000-0002-9969-0982)
- Erik Weyer (ORCID: https://orcid.org/0000-0003-4309-4337)
- Angus R. Simpson (ORCID: https://orcid.org/0000-0003-1633-0111)
- Lisa J. Blinco (ORCID: https://orcid.org/0000-0003-4593-5857)
- Ye Wang (ORCID: https://orcid.org/0000-0002-0123-1260)
Institutions
- The University of Melbourne (AU)
- South Australian Water Corporation (AU)
- The University of Adelaide (AU)
Publication Details
- Journal
- IEEE Transactions on Control Systems Technology
- Published
- 2024-10-18
- DOI
- https://doi.org/10.1109/tcst.2024.3477304
- Citations
- 3
- Primary Topic
- Water Systems and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.78