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Digital and Intelligent Systems for Renewable and Sustainable Energy Application

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

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 1309

Special Issue Editors


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Guest Editor
School of Computer Science and Electronic Engineering, the Nuclear Futures Institute, Bangor University, Bangor LL57 2DG, UK
Interests: advanced control system; mechatronics; renewable energy systems; sliding mode control and observation; environmental monitoring; signal processing
Special Issues, Collections and Topics in MDPI journals
École Nationale des Sciences Appliquées, Sidi Mohamed Ben Abdellah University, Fez BP 72, Morocco.
Interests: Solar Energy; Wind Energy; Smart Grid
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
1. Department of Electronics, Carleton University, Ottawa, ON K1S 5B6, Canada
2. Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USA
Interests: multi-objective optimization; energy/health-conscious mechatronics; robotics; autonomous systems; diagnosis/prognosis; electrified transportation; motor drives; energy storage
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The main objective of this Special Issue is to present high-quality works on the integration of digital and intelligent systems in renewable and sustainable energy, such as artificial intelligence, machine learning, data analytics, big data, cloud computing, blockchain, Internet of Things, and embedded systems. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes and new applications) are welcome. Authors are invited to submit manuscripts that present original and unpublished research in all areas related to digital and intelligent systems in renewable energy.

Energy efficiency in a digital scenario and fast computing methodologies have become one of the most vital parameters in determining the success of a product in the market. To stay globally competitive, every manufacturer and service provider invests huge amounts of money in research and development for artificial intelligence solutions in assisting the energy efficiency and sustainability of their products. Recently, artificial intelligence (AI), Internet of Things (IoT), big data analytics, machine learning, deep learning, cloud computing, and blockchain technologies have been intelligently applied with various applications in networking, manufacturing, building management, transportation, and shipping to build energy-efficient and sustainable systems.

This Special Issue focuses on recent advancements in product-based design and manufacturing for achieving energy efficiency using artificial intelligence technologies. Topics of interest for this Special Issue include but are not limited to:

  • Intelligent energy-efficient solutions for future applications;
  • AI and blockchain-assisted energy-efficient product designs;
  • Optimization of energy assets using machine learning and deep learning algorithms;
  • Smart IoT sensor design and optimal utilization in smart cities;
  • Industrial Revolution 4.0 focused automation using blockchain technologies in energy harvest (photovoltaic (PV), wind, solar, marine, batteries, electric vehicles (EVs));
  • Real-time energy resource management and efficient Internet of Medical Things;
  • Applications of artificial intelligence, blockchain IoT for sustainable manufacturing and service;
  • AI-based intelligent solutions for energy efficiency;
  • Artificial neural networks applied to energy systems;
  • Advanced control applied to energy systems;
  • Energy solutions to intelligent transportation systems;
  • Big-data-supported energy-efficient systems;
  • Energy-efficient cloud computing designs;
  • Energy-efficient fog networks;
  • Hardware optimization for energy efficiency;
  • Advanced sensor technologies for sustainable systems;
  • Future perspectives of energy efficient and sustainable products;
  • Digital quality monitoring of energy assets (photovoltaic (PV), wind, solar, marine, batteries, and electric vehicles (EVs)) for preventive/predictive management and cost optimization.

Dr. Hafiz Ahmed
Dr. Saad Motahhir
Dr. Hicham Chaoui
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. 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

  • wind energy
  • solar energy
  • digital technology
  • renewable energy systems
  • Industry 4.0
  • blockchain
  • energy efficiency
  • diagnostics and monitoring
  • artificial intelligence
  • machine learning

Published Papers

There is no accepted submissions to this special issue at this moment.
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