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

Deadline for manuscript submissions: closed (30 June 2019) | Viewed by 9174

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Prof. Dr. Isam Shahrour

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Civil and Geo-Environmental Laboratory, Lille University, 59650 Villeneuve d'Ascq, France
Interests: smart city; smart energy; smart water; smart infrastructures; civil engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Water and energy management constitutes a major challenge for cities. The question is how to ensure sustainable, safe, and high-quality water and energy services in cities subjected to increasing challenges such as high demographic growth, infrastructures ageing, and rapid change in the demand profile, water scarcity, climate change, energy transition, air pollution, and lack of public investment.

The objective of this Special Issue is to present scientific innovations and progresses in the field of water and energy management in urban areas, with a focus on innovative management methods with data from real cases or large experimentations. Papers reporting technological or/and social innovations are welcome.

We welcome submissions covering different areas, such as:

Energy: renewable energy in urban areas, energy storage, dynamic pricing, electrical vehicles, urban mobility, district heating, public lighting, energy transition, smart mobility, smart grids, smart buildings, resilient energy systems;
Water: floods, dynamic storm water management, water leaks, water pollution, water quality control, energy optimization in water distribution, integrated water management, sea water intrusion, smart water, resilient water systems;
The water-energy nexus in urban areas;
Asset management, predictive maintenance, investment priority, use of smart technology, GIS (Geographic Information System), BIM (Building Information Modeling), virtual and augmented reality;
Cybersecurity;
Utility tunnels;
The impact of urban water and energy systems on the environment (global warming, pollution, public health, biodiversity, etc.);
The governance of water and energy systems, innovation in the economic model, public-private partnership, the role of insurance, regulations evolutions, end-user involvement.

Prof. Dr. Isam Shahrour
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

water
energy
management
urban
resilience
optimal
security
service quality
demand
renewable
leak
contamination
smart grid
smart city

Published Papers (3 papers)

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Research

24 pages, 5669 KiB

Open AccessArticle

A Short-Term Data Based Water Consumption Prediction Approach

by Rafael Benítez, Carmen Ortiz-Caraballo, Juan Carlos Preciado, José M. Conejero, Fernando Sánchez Figueroa and Alvaro Rubio-Largo

Energies 2019, 12(12), 2359; https://0-doi-org.brum.beds.ac.uk/10.3390/en12122359 - 19 Jun 2019

Cited by 22 | Viewed by 2893

Abstract

A smart water network consists of a large number of devices that measure a wide range of parameters present in distribution networks in an automatic and continuous way. Among these data, you can find the flow, pressure, or totalizer measurements that, when processed with appropriate algorithms, allow for leakage detection at an early stage. These algorithms are mainly based on water demand forecasting. Different approaches for the prediction of water demand are available in the literature. Although they present successful results at different levels, they have two main drawbacks: the inclusion of several seasonalities is quite cumbersome, and the fitting horizons are not very large. With the aim of solving these problems, we present the application of pattern similarity-based techniques to the water demand forecasting problem. The use of these techniques removes the need to determine the annual seasonality and, at the same time, extends the horizon of prediction to 24 h. The algorithm has been tested in the context of a real project for the detection and location of leaks at an early stage by means of demand forecasting, and good results were obtained, which are also presented in this paper. Full article

(This article belongs to the Special Issue Urban Water and Energy Management)

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19 pages, 21959 KiB

Open AccessArticle

Automatic and Visual Processing Method of Non-Contact Monitoring for Circular Stormwater Sewage Tunnels Based on LiDAR Data

by Xiongyao Xie, Mingrui Zhao, Jiamin He and Biao Zhou

Energies 2019, 12(9), 1599; https://0-doi-org.brum.beds.ac.uk/10.3390/en12091599 - 26 Apr 2019

Cited by 9 | Viewed by 2921

Abstract

The application of Light Detection And Ranging (LiDAR) technology has become increasingly extensive in tunnel structure monitoring. The proposed processing method aims to carry out non-contact monitoring for circular stormwater sewage tunnels and provides an efficient workflow. This allows the automatic processing of raw point data and the acquisition of visualization results to analyze the health state of a tunnel within a short period of time. The proposed processing method employs a series of algorithms to extract the point cloud of a single tunnel segment without obvious noise by main three steps: axis acquisition, segment extraction, and denoising. The tunnel axis is extracted by fitting boundaries of the tunnel point cloud projection in the plane. With the guidance of the axis, the entire preprocessed tunnel point cloud is segmented by equal division to get a section of the tunnel point cloud which corresponds to a single tunnel segment. Then, the noise in every single point cloud segment is removed by clustering the algorithm twice, based on the distance and intensity. Finally, clean point clouds of tunnel segments are processed by an effective deformation extraction processor to determine the ovality and to get a three-dimensional visual deformation nephogram. The proposed method can significantly improve the efficiency of LiDAR data processing and extend the application of LiDAR technology in circular stormwater sewage tunnel monitoring. Full article

(This article belongs to the Special Issue Urban Water and Energy Management)

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17 pages, 5409 KiB

Open AccessArticle

Identification and Visualization of the Full-Ring Deformation Characteristics of a Large Stormwater Sewage and Storage Tunnel Using Terrestrial Laser Scanning Technology

by Zixin Zhang, Tong Yin, Xin Huang, Fan Zhang, Yeting Zhu and Wei Liu

Energies 2019, 12(7), 1304; https://0-doi-org.brum.beds.ac.uk/10.3390/en12071304 - 04 Apr 2019

Cited by 7 | Viewed by 2794

Abstract

Constructing deeply-buried stormwater sewage and storage tunnels is an effective method to mitigate the waterlogging and sewer overflow problems in modern cities. Prior to construction of such tunnels, a structural loading test is essential for acquiring the mechanical responses under complex loading conditions, such as cyclic inner hydraulic head, during which capturing the full-ring deformation of the tunnel lining is significant for a comprehensive understanding of the tunnel’s mechanical behaviors. This paper introduces the application of terrestrial laser scanning (TLS) technology in the full-scale structural loading tests of a large stormwater sewage and storage tunnel, which gives the full-ring deformation throughout the tests. A data processing methodology was developed to extract the key data points of the lining segments from the original data cloud by removing noise points and mitigating data jump, based on which the deformation of testing the lining segments at arbitrary locations can be calculated. Furthermore, a post-processing software was developed to visualize the full-ring deformation. The full-ring deformation at different loading conditions and its evolution under cyclic loading were captured. It is shown that the lining’s convergence deformation is more sensitive to the inner hydraulic head than to the external soil-water pressure, and the deformation cannot fully recover in a water-inflow-and-drainage cycle due to the presence of joints. Full article

(This article belongs to the Special Issue Urban Water and Energy Management)

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