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Sustainability
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Innovation in Renewable Energy Technologies
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Innovation in Renewable Energy Technologies

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

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 4623

Special Issue Editors

Prof. Dr. Andrea Toscani

E-Mail Website
Guest Editor
Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy
Interests: design of power converters and electric drives for industrial and consumer applications; fault diagnosis of electric motors and drives; aerospace and renewable energy applications with wide-bandgap (SiC, GaN) power devices
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Paolo Cova

E-Mail Website
Guest Editor
Department of Engineering and Architecture, University of Parma, Parma 43124, Italy
Interests: thermal management of electron devices and power converters; reliability of power electronics, from component to package, to assembly; electrothermal modeling of electron devices; renewable energy technologies
Dr. Nicola Delmonte

E-Mail Website
Guest Editor
Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy
Interests: smart city; power electronic; renewables; sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are inviting submissions to a new Energies Special Issue on “Innovation in Renewable Energy Technologies”. This Special Issue is focused mainly on ICT systems developed to more sustainably exploit renewable energies.

Research in the field of energy is becoming more and more challenging because sustainability aspects must be addressed. Reduction of air pollutants, waste, traditional energy, and costs are needed to develop more and more sustainable systems to produce, distribute, and use energy. Thus, researchers and designers of different fields are working on these issues to identify more feasible and affordable solutions, both at system and component levels.

An example of this holistic approach can be smart grids, where technological, environmental, and economic aspects must be considered together to optimize the system. At the component level, there are a lot of examples which can be used, from new energy carriers, to storage technologies and IoT applied to converters and loads.

This Special Issue is intended to give an effective contribution to highlight all innovations in renewable energy to generate, convert, distribute, store, and utilize electricity.

  • Numerical modeling of smart grids and their components;
  • Development of innovative power converters;
  • Development of new sensors, sensing techniques, and sensor concepts;
  • Solutions and techniques for renewable energy generation, conversion, distribution, storage, and use;
  • Renewable energy value chains;
  • New energy carriers;
  • Optimization methods for designing smart grids;
  • Methods for innovative optimized strategies and algorithms to manage, control, and maintain smart energy systems;
  • Innovative IoT solutions for renewable energy systems;
  • Big data, machine learning, and artificial intelligence to design, simulate, manage, and diagnose;
  • Life cycle assessment of innovative renewable energy solutions for electrical distribution.

Prof. Dr. Andrea Toscani
Prof. Dr. Paolo Cova
Prof. Dr. Nicola Delmonte
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

  • smart grid
  • renewable energy
  • power converter
  • energy generation
  • conversion
  • distribution
  • storage
  • IoT
  • life cycle assessment
  • smart maintenance

Published Papers (2 papers)

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Review

29 pages, 3161 KiB  
Review
Review of Machine Learning Techniques for Power Quality Performance Evaluation in Grid-Connected Systems
by Ramya Kuppusamy, Srete Nikolovski and Yuvaraja Teekaraman
Sustainability 2023, 15(20), 15055; https://0-doi-org.brum.beds.ac.uk/10.3390/su152015055 - 19 Oct 2023
Cited by 2 | Viewed by 1080
Abstract
In the current energy usage scenario, the demands on energy load and the tariffs on the usage of electricity are two main areas that require a lot of attention. Energy forecasting is an ideal solution that would help us to better understand future [...] Read more.
In the current energy usage scenario, the demands on energy load and the tariffs on the usage of electricity are two main areas that require a lot of attention. Energy forecasting is an ideal solution that would help us to better understand future needs and formulate solutions accordingly. Some important factors to investigate are the quantity and quality of smart grids as they are significantly influenced by the transportation, storage, and load management of energy. This research work is a review of various machine learning algorithms for energy grid applications like energy consumption, production, energy management, design, vehicle-to-grid transfers, and demand response. Ranking is performed with the help of key parameters and is evaluated using the Rapid Miner tool. The proposed manuscript uses various machine learning techniques for the evaluation of power quality performance to validate an efficient algorithm ranking in a grid-connected system for energy management applications. The use of renewable energy resources in grid-connected systems is more common in modern power systems. Universally, the energy usage sector (commercial and non-commercial) is undergoing an increase in demand for energy utilization that has substantial economic and ecological consequences. To overcome these issues, an integrated, ecofriendly, and smart system that meets the high energy demands is implemented in various buildings and other grid-connected applications. Among various machine learning techniques, an evaluation of seven algorithms—Naïve Bayes, artificial neural networks, linear regression, support vector machine, Q-learning, Gaussian mixture model, and principle component analysis—was conducted to determine which algorithm is the most effective in predicting energy balance. Among these algorithms, the decision tree, linear regression, and neural networks had more accurate results than the other algorithms used. As a result of this research, a proposal for energy forecast, energy balance, and management was compiled. A comparative statement of various algorithms concludes with results which suit energy management applications with high accuracy and low error rates. Full article
(This article belongs to the Special Issue Innovation in Renewable Energy Technologies)
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29 pages, 7174 KiB  
Review
Local Power Distribution—A Review of Nanogrid Architectures, Control Strategies, and Converters
by Danilo Santoro, Nicola Delmonte, Marco Simonazzi, Andrea Toscani, Nicholas Rocchi, Giovanna Sozzi, Paolo Cova and Roberto Menozzi
Sustainability 2023, 15(3), 2759; https://0-doi-org.brum.beds.ac.uk/10.3390/su15032759 - 03 Feb 2023
Cited by 5 | Viewed by 2914
Abstract
Environmental issues and the global need to extend sustainable access to electricity have fostered a huge amount of research in distributed generation by renewables. The challenges posed by the widespread deployment of distributed generation by renewables, such as intermittent power generation, low inertia, [...] Read more.
Environmental issues and the global need to extend sustainable access to electricity have fostered a huge amount of research in distributed generation by renewables. The challenges posed by the widespread deployment of distributed generation by renewables, such as intermittent power generation, low inertia, the need for energy storage, etc., call for the development of smart grids serving specific local areas or buildings, referred to as microgrids and nanogrids, respectively. This has led in the last decades to the proposal and actual implementation of a wide variety of system architectures and solutions, and along with that the issue of the power converters needed for interfacing the AC grid with DC micro- or nanogrids, and for DC regulation within the latter. This work offers an overview of the state of the art of research and application of nanogrid architectures, control strategies, and power converter topologies. Full article
(This article belongs to the Special Issue Innovation in Renewable Energy Technologies)
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