Special Issue "Renewable and Sustainable Energy: Modeling, Control, Modern Optimization and Multi Criteria Decision Making"

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

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Dr. Hegazy Rezk
E-Mail Website
Guest Editor
Electrical Engineering, College of Engineering - Wadi Aldwaser, Prince Sattam bin Abdulaziz University, Wadi Aldwaser, Saudi Arabia
Interests: renewable and sustainable energy; energy management; energy efficiency; modern optimization; modeling based on artificial intelligence
Special Issues and Collections in MDPI journals
Dr. Mokhtar Aly
E-Mail Website
Guest Editor
Electronics Engineering Department, Universidad Tecnica Federico Santa Maria, Valparaiso 2390123, Chile
Interests: renewable energy applications; reliability of power electronics systems; multilevel inverters; model predictive control; resilient microgrids; electric vehicles (EV)
Dr. Mohammad Ali Abdelkareem
E-Mail Website
Guest Editor
Sustainable and renewable energy engineering department, university of Sharjah, UAE
Interests: renewable energy; fuel cells; microbial fuel cells; energy storage; water desalination
Special Issues and Collections in MDPI journals
Dr. Ahmed Fathy
E-Mail Website
Guest Editor
Electrical Engineering, College of Engineering , Jouf University, Saudi Arabia
Interests: renewable energy optimization; optimal location of DGs in distribution networks; LFC; design of maximum power point trackers; applications of AI; modern optimization

Special Issue Information

Dear Colleagues,

Industrial advancement and rapid population growth have resulted in increasing fossil fuel usage that is limited in resources and has a severe environmental impact. The strength of this environmental impact has increased with global warming, and the health issues associated with are quite clear today. The consensus among scientists is that sustainable renewable energy sources with no or very low environmental impact are the best solution to this problem. Modeling and optimization are effectively used to solve complicated processes in a short time with minimum effort. Among the different modeling and optimization processes, Artificial Intelligence (AI) and modern optimization have exhibited excellent results in dealing with various applications in various research areas. Modeling based on AI and modern optimization methods is playing a key part in the industrial revolution, being extensively used by practicing engineers to solve complicated problems. Moreover, applying modern control systems can lead to enhancing energy efficiency, reliability, stability, and energy security of renewable and sustainable energy systems. Model predictive control (MPC) methods can achieve fast, precise, and multiobjective control tasks for renewable energy systems. By contrast, multicriteria decision making (MCDM) problems are basically fundamental issues in various fields, including renewable and sustainable energy. MCDM models provide a useful way to model several real-world problems, and they are extensively used in many engineering applications, such as energy efficiency, sustainable development, and so forth. The Special Issue provides a platform for researchers and practitioners from both academia and industry in addition to experts in the area of modern optimizations, control systems, artificial intelligence, and decision making applied to renewable and sustainable energy. Papers published in this Special Issue describe original works in different topics in both science and engineering, such as: soft computing, neural networks, fuzzy logic, multicriteria decision making, etc.

We cordially invite you to submit your original contributions to this Special Issue, entitled: “Renewable and Sustainable Energy: Modeling, Control, Modern Optimization and Multicriteria Decision Making”. This is a Special Issue of Sustainability MDPI, an international peer-reviewed open access journal covered by various databases, such as WOS and SCOPUS. The present Special Issue aims to collect innovative solutions and experimental research supported by appropriate modeling and design, but also state-of-the-art studies, in the following topics:

  • Modeling based on artificial intelligence
  • Decision-making methods for sustainable development
  • Modern optimization
  • Renewable energy systems
  • Hydrogen and fuel cell
  • Energy storage systems
  • Advanced control systems
  • Model predictive control
  • Energy management strategies
  • Neural networks
  • Energy efficiency

Dr. Hegazy Rezk
Dr. Mokhtar Aly
Dr. Mohammad Ali Abdelkareem
Dr. Ahmed Fathy
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 papers will be 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 1900 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

  • renewable energy
  • energy efficiency
  • model predictive control
  • artificial intelligence
  • decision making
  • modern optimization
  • energy management
  • solar energy
  • wind energy
  • biomass
  • fuel cell

Published Papers (2 papers)

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Research

Article
Multicriteria Decision-Making to Determine the Optimal Energy Management Strategy of Hybrid PV–Diesel Battery-Based Desalination System
Sustainability 2021, 13(8), 4202; https://doi.org/10.3390/su13084202 - 09 Apr 2021
Viewed by 445
Abstract
This paper identifies the best energy management strategy of hybrid photovoltaic–diesel battery-based water desalination systems in isolated regions using technical, economic and techno–economic criteria. The employed procedures include Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order Preference by Similarity to Ideal [...] Read more.
This paper identifies the best energy management strategy of hybrid photovoltaic–diesel battery-based water desalination systems in isolated regions using technical, economic and techno–economic criteria. The employed procedures include Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as tools for the solution. Twelve alternatives, containing three–four energy management strategies; four energy management strategies, load following (LF), cycle charging (CC), combined LF–CC, and predictive strategy; and three different sizes of brackish water reverse osmosis (BWRO) water desalination units, BWRO-150, BWRO-250, and BWRO-500, are investigated with capacity of 150, 250, and 500 m3/day, respectively. Eight attributes comprising different technical and economic metrics are considered during the evaluation procedure. HOMER Pro® software is utilized to perform the simulation and optimization. The main findings confirmed that the best energy management strategies are predictive strategies and the reverse osmosis (RO) unit’s optimal size is RO-250. For such an option, the annual operating cost and initial costs are $4590 and $78,435, respectively, whereas the cost of energy is $0.156/kWh. The excess energy and unmet loads are 27,532 kWh and 20.3 kWh, respectively. The breakeven grid extension distance and the amount of CO2 are 6.02 km and 14,289 kg per year, respectively. Compared with CC–RO-150, the amount of CO2 has been sharply decreased by 61.2%. Full article
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Article
Dynamic Voltage Restorer Integrated with Photovoltaic-Thermoelectric Generator for Voltage Disturbances Compensation and Energy Saving in Three-Phase System
Sustainability 2021, 13(6), 3511; https://doi.org/10.3390/su13063511 - 22 Mar 2021
Viewed by 420
Abstract
The dynamic voltage restorer (DVR) combined with a photovoltaic–thermoelectric generator (PV-TEG) system is proposed for voltage disturbance compensation in the three-phase four-wire distribution system. The PV-TEG hybrid energy source is used in the DVR system to improve the system ability for deep and [...] Read more.
The dynamic voltage restorer (DVR) combined with a photovoltaic–thermoelectric generator (PV-TEG) system is proposed for voltage disturbance compensation in the three-phase four-wire distribution system. The PV-TEG hybrid energy source is used in the DVR system to improve the system ability for deep and long-period power quality disturbance compensation. In addition, the DVR will save grid energy consumption when the hybrid PV-TEG module generates sufficient power to meet the load demand. An enhanced variable factor adaptive fuzzy logic controller (VFAFLC)-based maximum power point tracking (MPPT) control scheme is proposed to extract the maximum possible power from the PV module. Since the PV and TEG combine a hybrid energy source for generating power, the DVR can work efficiently for the voltage sag/swell, outage compensation, and energy conservation mode with minimum energy storage facilities. The in-phase compensation method and the three-leg voltage source inverter (VSI) circuit are chosen in the present system for better voltage and/or power compensation. To confirm the effectiveness of the proposed hybrid PV-TEG integrated DVR system, a simulation-based investigation is carried out with four different operational modes with MATLAB software. The study results confirm that the proposed DVR system can compensate power quality disturbances of the three-phase load with less total harmonics distortion (THD) and will also work efficiently under energy conservation mode to save grid energy consumption. Moreover, the proposed VFAFLC-based control technique performs better to achieve the maximum power point (MPP) quickly and accurately, thereby improving the efficiency of the hybrid energy module. Full article
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