sustainability-logo

Journal Browser

Journal Browser

Modeling, Control and Optimization for Smart Water Systems

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Water Management".

Deadline for manuscript submissions: 1 June 2024 | Viewed by 906

Special Issue Editor


E-Mail Website
Guest Editor
Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
Interests: modeling, control and optimisation for water systems; automatic control; model predictive control

Special Issue Information

Dear Colleagues,

Water is a fundamental resource for human life, and even more so in the current context of severe climate change. A growing attention towards the environmental impact of water use is pushing water utilities to optimise its management.

With the rise of the Water 4.0 approach, i.e., the application of the wider Industry 4.0 approach to the water industry, water systems are made smart, thanks to the spread of advanced sensors and actuators throughout the whole plant, as well as their integration in the Industrial Internet of Things network. This unlocks access to a previously inaccessible amount of data, as well as to unprecedented communication capabilities, thus opening up a new range of possibilities for research and development.

This Special Issue, entitled “Modeling, Control and Optimization for Smart Water Systems”, aims at collecting cutting-edge contributions proposing ways to effectively and efficiently exploit the advantages offered by smart water systems, with the final goal of making water management more sustainable.

Due to the strongly cross-disciplinary character of the Water 4.0 approach, this Special Issues is addressed to wide range research communities. A list of possible  topics includes, but is not limited to:

  • Optimal design of Smart Water Systems;
  • Hydraulic and data driven modeling of Smart Water Systems;
  • Development and use of Smart Water Systems digital twins;
  • Analysis and modeling of water demand;
  • Real time control;
  • Pump scheduling;
  • Energy recovery;
  • Monitoring and control of water quality;
  • Leakage detection;
  • Fault detection, isolation and recovery;
  • Decision support systems.

Both methodological and case-study contributions are welcome.

Dr. Giacomo Galuppini
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • water systems
  • data analysis
  • machine learning
  • modeling
  • control
  • optimization
  • decision support systems
  • fault detection
  • leakage detection
  • water quality
  • energy recovery

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

31 pages, 5933 KiB  
Article
Assessment of Peak Water Usage among Residential Consumers across Several Drinking Water Service Areas
by Alex J. Garzón-Orduña, Oscar E. Coronado-Hernández, Rafael O. Ortiz, Alfonso Arrieta-Pastrana and Vicente S. Fuertes-Miquel
Sustainability 2024, 16(4), 1601; https://doi.org/10.3390/su16041601 - 14 Feb 2024
Viewed by 653
Abstract
Public drinking water service providers must comprehensively understand and effectively characterise user demands, especially during peak hours, which not only impact the maximum demand within the distribution network but also determine the dimensions of interior networks within buildings. Residential consumers show different consumption [...] Read more.
Public drinking water service providers must comprehensively understand and effectively characterise user demands, especially during peak hours, which not only impact the maximum demand within the distribution network but also determine the dimensions of interior networks within buildings. Residential consumers show different consumption patterns based on socioeconomic factors, spatial location, climatic conditions and the consistency and quality of service delivered by public service providers. This study focused on assessing 1,317,584 users distributed across four distinct service areas in Bogotá, Colombia. To achieve this, a stratified random sampling of 1233 residential subscribers was conducted and 320 reference digital Y290 Aquabus micro-meters were installed to characterise the four service areas. The installations were grouped into sets of 320 users until the entire sample of 1233 subscribers was encompassed. The results demonstrated that the rational method provided the most accurate fit for estimating the probable maximum flow rates compared to the values measured and, consequently, is the most suitable method for application within the region of interest. However, whereas the Hunter Unal method displayed a reasonable fit, it tended to underestimate the size of internal networks within buildings. The remaining methods, such as the British, square root, simultaneity, Hunter, NTC 1500 Hunter and Chilean methods, did not yield significant adjustments and tended to overestimate the probable maximum flow rates as well as the internal networks within buildings. The results indicate that, depending on the method used to calculate the probable maximum flow or design flow of the internal network, there can be a deviation factor when compared to the actual peak flow measured (real maximum flow). This deviation factor ranges from 0.79 (calculated less than measured) to 3.77 (calculated greater than measured). Additionally, a sizing case study was conducted, which involved applying all methods to a scenario involving a residential user. This study aimed to determine the variation expected in the estimation of the diameter of the supply pipe to the internal network when using the flow results from different methods. This analysis serves to conclude the research. Full article
(This article belongs to the Special Issue Modeling, Control and Optimization for Smart Water Systems)
Show Figures

Figure 1

Back to TopTop