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Special Issue "Sustainable Energy Consumption 2021"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: closed (15 December 2021) | Viewed by 3074

Special Issue Editors

GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, P-4200-072 Porto, Portugal
Interests: artificial intelligence; decision-support systems; energy markets; machine learning; smart buildings; virtual power players
Special Issues, Collections and Topics in MDPI journals
GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto (P.PORTO), P-4200-465 Porto, Portugal
Interests: artificial intelligence; demand response; electric vehicles; electricity markets; power and energy systems; renewable and sustainable energy; smart grids
Special Issues, Collections and Topics in MDPI journals
Department of Electrical Sustainable Energy, Delft University of Technology, 2628 CD Delft, The Netherlands
Interests: power grids; power engineering computing; frequency control; power system security; power system interconnection; power system simulation; optimization; power generation control; HVDC power
Special Issues, Collections and Topics in MDPI journals
Department of System Design Engineering, Faculty of Science and Technology, Keio University, Kanagawa 223-8522, Japan
Interests: automated metering infrastructure; distributed systems; edge computing; energy data services; sensor networks; smart buildings; smart cities
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Energy sustainability is a key challenge for a developed and sustainable world. The use of renewable energy has significantly increased over the past several years, bringing new technical and commercial challenges to the energy sector.

Consumers are key players in this context, as demand flexibility is crucial to coping with the intermittency of most renewable energy sources, such as wind and sun. Demand-active participation is particularly important to ensuring the efficient use of the available energy at local and global levels.

The Special Issue “Sustainable Energy Consumption”, published in 2019, addressed the different perspectives of energy consumption and demand for ensuring energy sustainability, increased energy efficiency, and reasonable energy costs. It published five papers evidencing the relevance of the Special Issue topics, which are gaining more and more importance.

We are now launching a new Special Issue, “Sustainable Energy Consumption 2021”, as a continuation of the previous one, with a particular focus on the use of artificial intelligence to solve the main challenges in the field. We invite papers on innovative scientific and technical developments, sound case studies, and reviews which are relevant and/or related to “Sustainable Energy Consumption”. Selected papers are expected to propose models, methods, and tools that address demand response, demand-side management, consumption analysis, and profiling, as well as different aspects related to energy demand and its management in the scope of sustainable energy systems. Papers using artificial intelligence techniques—namely, machine learning—are particularly welcome. In this sense, the topics of interest also include smart grids, renewable-based generation, energy storage systems, distributed energy resources, energy-efficient buildings, as well as electric and hybrid vehicles, as long as the energy consumption aspects are considered.

Prof. Dr. Carlos Ramos
Prof. Dr. Zita Vale
Prof. Dr. Peter Palensky
Prof. Dr. Hiroaki Nishi
Guest Editors

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

  • active consumers
  • artificial intelligence approaches for sustainable energy consumption
  • data analytics and data mining for sustainable energy consumption
  • demand response
  • demand-side management
  • electric and hybrid vehicles
  • energy efficiency
  • energy-efficient buildings
  • energy management
  • energy policy
  • energy storage
  • load flexibility
  • machine-learning models for sustainable energy consumption
  • renewable energy
  • smart grids

Related Special Issue

Published Papers (1 paper)

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Review

Review
A Pragmatic Investigation of Energy Consumption and Utilization Models in the Urban Sector Using Predictive Intelligence Approaches
Energies 2021, 14(13), 3900; https://doi.org/10.3390/en14133900 - 29 Jun 2021
Cited by 19 | Viewed by 2226
Abstract
Energy consumption is a crucial domain in energy system management. Recently, it was observed that there has been a rapid rise in the consumption of energy throughout the world. Thus, almost every nation devises its strategies and models to limit energy usage in [...] Read more.
Energy consumption is a crucial domain in energy system management. Recently, it was observed that there has been a rapid rise in the consumption of energy throughout the world. Thus, almost every nation devises its strategies and models to limit energy usage in various areas, ranging from large buildings to industrial firms and vehicles. With technological advancements, computational intelligence models have been successfully contributing to the prediction of the consumption of energy. Machine learning and deep learning-based models enhance the precision and robustness compared to traditional approaches, making it more reliable. This article performs a review analysis of the various computational intelligence approaches currently being utilized to predict energy consumption. An extensive survey procedure is conducted and presented in this study, and relevant works are discussed. Different criteria are considered during the aggregation of the relevant studies relating to the work. The author’s perspective, future trends and various novel approaches are also presented as a part of the discussion. This article thereby lays a foundation stone for further research works to be undertaken for energy prediction. Full article
(This article belongs to the Special Issue Sustainable Energy Consumption 2021)
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