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Energies
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Smart Water Networks in Urban Environments
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Smart Water Networks in Urban Environments

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (31 March 2018) | Viewed by 7468

Special Issue Editors

Prof. Dr. Yacine Rezgui

E-Mail Website
Guest Editor
BRE Institute of Sustainable Engineering, Cardiff University, Cardiff CF10 3AT, UK
Interests: architectural and civil engineering; computing; artificial intelligence; building energy; energy and environment; sustainability
Special Issues, Collections and Topics in MDPI journals
Dr. Tom Beach

E-Mail Website
Guest Editor
Cardiff School of Engineering, Cardiff University, Queen's Buildings, The Parade CARDIFF, Wales CF24 3AA, UK
Interests: specification and implementation of building/district/city data storage; Internet of Things (IoT) and its application to the monitoring and control of the built environment; data analytics, including machine learning and artificial intelligence; application of cloud/distributed computing to data storage and processing for built environment applications; semantics of data within the built environment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Water network operators are currently facing key challenges; growing water demand caused by climate change, urbanization and population growth and increasing requirements to make water networks more sustainable and resilient. ICT technologies are key tools for solving these challenges, and the application of ICT technologies to water networks and their management is currently gathering increasing research interest. Delivering these smart water network technologies is vital in achieving long term sustainability and resilience for the infrastructure delivering water to our urban environments. Achieving success is an inter-disciplinary challenge requiring developments in the areas of ICT, data science, as well as the social sciences.

This Special Issue aims to publish high-quality research articles on the latest developments in smart water networks in urban environments—from design through to operation, focusing on technology, policies and practices, considering both clean and/or waste water networks. Articles addressing the interrelationships between traditionally disparate domains are particularly welcome. Topics include, but are not limited to, the following:

  • Energy efficiency of urban water networks.
  • Urban water management within smart cities.
  • Demand management of urban water sources.
  • Water network decision support.
  • Intelligent design of new/refurbished water networks.
  • Optimization of water networks.
  • Smart management of clean and waste water networks.
  • Ensuring resilience of water networks through smart water technologies.
  • Intelligent solutions to achieving increased fault tolerance or fault detection.
  • Embedding intelligence within water networks, i.e., intelligent valves/pumps.
Prof. Dr. Yacine Rezgui
Dr. Tom Beach
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. Energies 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 2600 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

  • Smart Water
  • Water Network Optimisation
  • Demand Management in Water Networks
  • Decision Support
  • Water Network Resilience

Published Papers (2 papers)

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Research

20 pages, 1072 KiB  
Article
Economic Model Predictive Control with Nonlinear Constraint Relaxation for the Operational Management of Water Distribution Networks
by Ye Wang, Teodoro Alamo, Vicenç Puig and Gabriela Cembrano
Energies 2018, 11(4), 991; https://doi.org/10.3390/en11040991 - 19 Apr 2018
Cited by 9 | Viewed by 2663
Abstract
This paper presents the application of an economic model predictive control (MPC) for the operational management of water distribution networks (WDNs) with periodic operation and nonlinear constraint relaxation. In addition to minimizing operational costs, the proposed approach aims to reduce the computational load [...] Read more.
This paper presents the application of an economic model predictive control (MPC) for the operational management of water distribution networks (WDNs) with periodic operation and nonlinear constraint relaxation. In addition to minimizing operational costs, the proposed approach aims to reduce the computational load and to improve the implementation efficiency associated with the nonlinear nature of the MPC problem. The behavior of the WDN is characterized by a set of difference-algebraic equations, where the relation of hydraulic pressure/head and flow in interconnected pipes is nonlinear. Specifically, the considered WDN model includes two categories of nonlinear algebraic equations for unidirectional and bidirectional flows in pipes, respectively. In this paper, we propose an iterative algorithm to relax these nonlinear algebraic equations into a set of linear inequality constraints that will be implemented in the economic MPC design, which improves the implementation efficiency and meanwhile optimizes the economic performance. Finally, the proposed strategy is applied to a well-known benchmark of the Richmond WDN. The closed-loop simulation results are shown and the proposed strategy is also compared with a nonlinear economic MPC using several key performance indexes. Full article
(This article belongs to the Special Issue Smart Water Networks in Urban Environments)
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21 pages, 1953 KiB  
Article
Multi-Model Prediction for Demand Forecast in Water Distribution Networks
by Rodrigo Lopez Farias, Vicenç Puig, Hector Rodriguez Rangel and Juan J. Flores
Energies 2018, 11(3), 660; https://doi.org/10.3390/en11030660 - 15 Mar 2018
Cited by 22 | Viewed by 4427
Abstract
This paper presents a multi-model predictor called Qualitative Multi-Model Predictor Plus (QMMP+) for demand forecast in water distribution networks. QMMP+ is based on the decomposition of the quantitative and qualitative information of the time-series. The quantitative component (i.e., the daily consumption prediction) is [...] Read more.
This paper presents a multi-model predictor called Qualitative Multi-Model Predictor Plus (QMMP+) for demand forecast in water distribution networks. QMMP+ is based on the decomposition of the quantitative and qualitative information of the time-series. The quantitative component (i.e., the daily consumption prediction) is forecasted and the pattern mode estimated using a Nearest Neighbor (NN) classifier and a Calendar. The patterns are updated via a simple Moving Average scheme. The NN classifier and the Calendar are executed simultaneously every period and the most suited model for prediction is selected using a probabilistic approach. The proposed solution for water demand forecast is compared against Radial Basis Function Artificial Neural Networks (RBF-ANN), the statistical Autoregressive Integrated Moving Average (ARIMA), and Double Seasonal Holt-Winters (DSHW) approaches, providing the best results when applied to real demand of the Barcelona Water Distribution Network. QMMP+ has demonstrated that the special modelling treatment of water consumption patterns improves the forecasting accuracy. Full article
(This article belongs to the Special Issue Smart Water Networks in Urban Environments)
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