Nothing Special   »   [go: up one dir, main page]
Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Electrical Engineering and Systems Science > Systems and Control

arXiv:2408.07696 (eess)
[Submitted on 14 Aug 2024]

Title:Model-Based Control of Water Treatment with Pumped Water Storage

Authors:Ryan Mauery, Margaret Busse, Ilya Kovalenko
View PDF HTML (experimental)
Abstract:Water treatment facilities are critical infrastructure they must accommodate dynamic demand patterns without system disruption. These patterns can be scheduled, such as daily residential irrigation, or unexpected, such as demand spikes from withdrawals for fire management. The critical necessity of clean, safe, and reliable water requires water treatment control strategies that are insensitive to disturbances to guarantee that demand will be met. One essential problem in achieving this is the minimization of energy costs in the process of meeting water demand, especially as the need for decarbonization persists. This work develops a control-oriented hydraulic model of a water treatment facility with integrated pumped storage and introduces a model predictive control strategy for scheduling treatment plant system operations to minimize greenhouse gas emissions and safely meet water demand.
Comments: 6 pages, 6 figures, 2 tables. Accepted for MECC 2024
Subjects: Systems and Control (eess.SY)
Cite as: arXiv:2408.07696 [eess.SY]
  (or arXiv:2408.07696v1 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.2408.07696

Submission history

From: Ryan Mauery [view email]
[v1] Wed, 14 Aug 2024 17:52:29 UTC (779 KB)
Full-text links:

Access Paper:

license icon view license
Current browse context:
eess.SY
< prev   |   next >
new | recent | 2024-08
Change to browse by:
cs
cs.SY
eess

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)