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Recent Developments in the Renewable and Sustainable Energies
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Recent Developments in the Renewable and Sustainable Energies

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

Deadline for manuscript submissions: closed (30 October 2021) | Viewed by 12173

Special Issue Editor

Dr. Noradin Ghadimi

grade E-Mail Website
Guest Editor
Department of Industrial Engineering, Ankara Yıldırım Beyazıt University (AYBU), Ankara 06010, Turkey
Interests: energy storage; batteries; power electronics; renewable energy resources; power system applications; smart and microgrids
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Renewable energy is energy that comes from renewable or recyclable sources and can be replaced by natural resources in the short term, such as sunlight, wind, rain, tidal, and the thermal heat of the earth. Not only have many renewable energy applications been done as part of large-scale projects, but these technologies are also suitable for use in rural, remote and developing countries. Renewable energies have the potential to bring the poorest countries to a high level of prosperity. The output of the most renewable energy sources has several advantages: It can convert electricity into heat (which can generate more heat than fossil fuels). It can also convert electricity into mechanical energy that has high efficiency and does not generate pollution during consumption. In addition, the use of renewable energies is more efficient and results in a significant reduction in the primary energy requirements due to the low losses in the compact cycle (fossil power plants typically have between 40% and 65% losses). Renewable energy systems become more efficient and cheaper every day. Their contribution to overall energy consumption is increasing rapidly. It is expected that increasing the use of renewable and clean energies will be the end of the consumption of fossil fuels by 2020. However, low reliability due to the nature of uncertain and volatile production of renewable resources is among the most important disadvantages of these resources. Based on the explained details, the main purpose of this Special issue is to bring about different solutions to the explained problems and to produce a safe resource based on different methods and strategies in producing the renewable and sustainable energies. This Special Issue looks to study different applications of “Recent Developments in the Renewable and Sustainable Energies”.

Dr. Noradin Ghadimi
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. 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

  • soft computing in the renewable energies
  • economics of renewable energy
  • environmental regulation and valuation
  • applications of different technologies in sustainability
  • economics of renewable resource
  • microgrids
  • forecasting

Published Papers (3 papers)

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Research

17 pages, 3449 KiB  
Article
Optimization of PEMFC Model Parameters Using Meta-Heuristics
by Saeideh Mahdinia, Mehrdad Rezaie, Marischa Elveny, Noradin Ghadimi and Navid Razmjooy
Sustainability 2021, 13(22), 12771; https://doi.org/10.3390/su132212771 - 18 Nov 2021
Cited by 78 | Viewed by 2634
Abstract
The present study introduces an economical–functional design for a polymer electrolyte membrane fuel cell system. To do so, after introducing the optimization problem and solving the problem based on the presented equations in the fuel cell, a cost model is presented. The final [...] Read more.
The present study introduces an economical–functional design for a polymer electrolyte membrane fuel cell system. To do so, after introducing the optimization problem and solving the problem based on the presented equations in the fuel cell, a cost model is presented. The final design is employed for minimizing the construction cost of a 50 kW fuel cell stack, along with the costs of accessories regarding the current density, stoichiometric coefficient of the hydrogen and air, and pressure of the system as well as the temperature of the system as optimization parameters. The functional–economic model is developed for the studied system in which all components of the system are modeled economically as well as electrochemically–mechanically. The objective function is solved by a newly improved metaheuristic technique, called converged collective animal behavior (CCAB) optimizer. The final results of the method are compared with the standard CAB optimizer and genetic algorithm as a popular technique. The results show that the best optimal cost with 0.1061 $/kWh is achieved by the CCAB. Finally, a sensitivity analysis is provided for analyzing the consistency of the method. Full article
(This article belongs to the Special Issue Recent Developments in the Renewable and Sustainable Energies)
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34 pages, 6310 KiB  
Article
Analyzing a Decade of Wind Turbine Accident News with Topic Modeling
by Gürdal Ertek and Lakshmi Kailas
Sustainability 2021, 13(22), 12757; https://doi.org/10.3390/su132212757 - 18 Nov 2021
Cited by 13 | Viewed by 7164
Abstract
Despite the significance and growth of wind energy as a major source of renewable energy, research on the risks of wind turbines in the form of accidents and failures has attracted limited attention. Research that applies data analytics methodologically in this context is [...] Read more.
Despite the significance and growth of wind energy as a major source of renewable energy, research on the risks of wind turbines in the form of accidents and failures has attracted limited attention. Research that applies data analytics methodologically in this context is scarce. The research presented here, upon construction of a text corpus of 721 selected wind turbine accident and failure news reports, develops and applies a custom-developed data analytics framework that integrates tabular analysis, visualization, text mining, and machine learning. Topic modeling was applied for the first time to identify and classify recurring themes in wind turbine accident news, and association mining was applied to identify contextual terms associated with death and injury. The tabular and visual analyses relate accidents to location (offshore vs. onshore), wind turbine life cycle phases (transportation, construction, operation, and maintenance), and the incidence of death and injury. As one of the insights, more incidents were found to occur during operation and transportation. Through topic modeling, topics associated most with deaths and injuries were revealed. The results could benefit wind turbine manufacturers, service providers, energy companies, insurance companies, government bodies, non-profit organizations, researchers, and other stakeholders in the wind energy sector. Full article
(This article belongs to the Special Issue Recent Developments in the Renewable and Sustainable Energies)
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12 pages, 2814 KiB  
Article
A Short-Term Power Output Forecasting Based on Augmented Naïve Bayes Classifiers for High Wind Power Penetrations
by Gyeongmin Kim and Jin Hur
Sustainability 2021, 13(22), 12723; https://doi.org/10.3390/su132212723 - 17 Nov 2021
Cited by 2 | Viewed by 1407
Abstract
Renewable-power-generating resources can provide unlimited clean energy and emit at most minute amounts of air pollutants and greenhouse gases, whereas fossil fuels are contributing to environmental pollution problems and climate change. The share of global power capacity comprising renewable-power-generating resources is increasing. However, [...] Read more.
Renewable-power-generating resources can provide unlimited clean energy and emit at most minute amounts of air pollutants and greenhouse gases, whereas fossil fuels are contributing to environmental pollution problems and climate change. The share of global power capacity comprising renewable-power-generating resources is increasing. However, due to the variability and uncertainty of wind resources, predicting the power output of these resources remains a key problem that must be resolved to establish stable power system operation and planning. In this study, we propose an ensemble prediction model for wind-power-generating resources based on augmented naïve Bayes classifiers. To select the principal component that affects the wind power outputs from among various meteorological factors, such as temperature, wind speed, and wind direction, prediction of wind-power-generating resources was performed using multiple linear regression (MLR) and a naïve Bayes classification model based on the selected meteorological factors. We proposed applying the analogue ensemble (AnEn) algorithm and the ensemble learning technique to predict the wind power. To validate this proposed hybrid prediction model, we analyzed empirical data from the wind farm of Jeju Island in South Korea and found that the proposed model has lower error than the single prediction models. Full article
(This article belongs to the Special Issue Recent Developments in the Renewable and Sustainable Energies)
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