Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.5
Journals
Applied Sciences
Special Issues
Smart Buildings for Decarbonised Energy Systems
applsci-logo
Submit to Applied Sciences Review for Applied Sciences Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Smart Buildings for Decarbonised Energy Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: closed (31 July 2019) | Viewed by 2969

Special Issue Editor

Dr. Andy Wright

E-Mail Website
Guest Editor
Institute of Energy and Sustainable Development (IESD), School of Engineering and Sustainable Development, De Montfort University, Leicester LE1 9BH, UK
Interests: energy in buildings; climate change and buildings; modelling; monitoring buildings; building retrofit
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Climate change, poor air quality, resource depletion, and energy security concerns are driving a revolution in the world’s energy systems. Buildings account for about one third of final energy use globally, and almost a fifth of energy-related greenhouse gas emissions. Decarbonisation of heating includes a shift from gas, to electric heat pumps or low carbon district heating. In parallel, there is a shift from fossil fuels for road transport to electric battery vehicles. Buildings are evolving from passive energy consumers to active participants of the energy system, with on-site low carbon generation, storage, charging of vehicles, and the ability to modify their demand on the grid. Advances in information technology provide opportunities for data capture and analysis of buildings and energy systems, facilitating 'smart' approaches to their management. These changes create multiple challenges across many disciplines for the design of buildings, their services, and energy system providers. The aim of this Special Issue is to bring together up-to-date research on the interaction of buildings with modern, decarbonising energy systems. This includes, but is not limited to:

  • Effective management of low carbon district heating
  • Electricity demand shaping by buildings on smart grids
  • Generation and storage of heat and electricity on site to reduce peak demands
  • Impact and management of vehicle charging on domestic supplies
  • Use of heat pumps and grid interactions
  • Management of smart grids in relation to buildings
  • Integration of community renewable energy for local consumption and with the grid

Dr. Andrew Wright
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. Applied Sciences 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.

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

17 pages, 762 KiB  
Article
Using Different ML Algorithms and Hyperparameter Optimization to Predict Heat Meters’ Failures
by Przemysław Pałasz and Radosław Przysowa
Appl. Sci. 2019, 9(18), 3719; https://doi.org/10.3390/app9183719 - 6 Sep 2019
Cited by 8 | Viewed by 2646
Abstract
The need to increase the energy efficiency of buildings, as well as the use of local renewable heat sources has caused heat meters to be used not only to calculate the consumed energy, but also for the active management of central heating systems. [...] Read more.
The need to increase the energy efficiency of buildings, as well as the use of local renewable heat sources has caused heat meters to be used not only to calculate the consumed energy, but also for the active management of central heating systems. Increasing the reading frequency and the use of measurement data to control the heating system expands the requirements for the reliability of heat meters. The aim of the research is to analyze a large set of meters in the real network and predict their faults to avoid inaccurate readings, incorrect billing, heating system disruption, and unnecessary maintenance. The reliability analysis of heat meters, based on historical data collected over several years, shows some regularities, which cannot be easily described by physics-based models. The failure rate is almost constant and does depend on the past, but is a non-linear combination of state variables. To predict meters’ failures in the next billing period, three independent machine learning models are implemented and compared with selected metrics, because even the high performance of a single model (87% true positive for neural network) may be insufficient to make a maintenance decision. Additionally, performing hyperparameter optimization boosts the models’ performance by a few percent. Finally, three improved models are used to build an ensemble classifier, which outperforms the individual models. The proposed procedure ensures the high efficiency of fault detection (>95%), while maintaining overfitting at the minimum level. The methodology is universal and can be utilized to study the reliability and predict faults of other types of meters and different objects with the constant failure rate. Full article
(This article belongs to the Special Issue Smart Buildings for Decarbonised Energy Systems)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop