Special Issue "Recent Optimization Methodologies of Energy Systems Based on Renewable Energy"

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

Deadline for manuscript submissions: 15 March 2022.

Special Issue Editor

Dr. Akbar Maleki
E-Mail Website
Guest Editor
Faculty of Mechanical Engineering, Shahrood University of Technology, Shahrood 3619995161, Iran
Interests: hybrid energy system; renewable energy; solar energy; energy optimization

Special Issue Information

Dear Colleagues,

The growing world population, mounting concerns regarding global warming due to the emission of greenhouse gases, and the possibility of depletion of fossil fuel sources in the near future necessitate the development of renewable energy systems. In this regard, the utilization of renewable energy sources for power generation and other purposes such as heating, cooling, and desalination has recently developed. Several approaches have been adopted to facilitate the modeling of renewable energy systems. These models utilize conventional computational methods or employ novel approaches. There are different advantages in using models, instead of experimental studies, such as lower time consumption, more cost effectiveness, environmental friendliness, and reliability. To achieve this aim, optimization methodologies of energy systems is important. Due to the importance of developing optimization methodologies of energy systems based on renewable energy, this Special Issue focuses on this topic. In this regard, high-quality studies that concentrate on recent optimization methodologies of energy systems based on renewable energy are invited to be submitted to the present Special Issue. The main interest of the present issue is the publication of both review and original articles in related fields. The most attractive topics are:

  • Optimization methodologies based on single objective function of energy systems;
  • Optimization methodologies based on multi objective functions of energy systems;
  • Single optimization algorithm for energy systems: particle swarm optimization; artificial bee swarm optimization; genetic algorithm; tabu search; simulated annealing algorithm; chaotic search; harmony search; etc.;
  • Hybrid optimization algorithm for energy systems;
  • Artificial techniques based on the genetic algorithm, particle swarm optimization, ant colony optimization, etc., for the optimization of energy systems;
  • Applications of artificial intelligence in the optimization of renewable energy systems;
  • Optimization and predictive models for properties of materials applicable in renewable energy systems;
  • Optimization models applicable for predicting the performance and reliability of clean energy systems;
  • Energy systems based on renewable energy sources (solar, wind, hydroelectric, geothermal, ocean, hydrogen, and biomass);
  • Recent optimization methodologies for hybrid renewable energy systems with different energy sources;
  • Optimization of multigeneration systems based on renewable energy sources.

In addition to the abovementioned topics, high-quality articles in relevant fields will be considered for publication.

Dr. Akbar Maleki
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 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 systems
  • optimization methodologies
  • hybrid optimization algorithms
  • energy systems
  • energy efficiency
  • metaheuristic type methods

Published Papers (1 paper)

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Research

Article
Parameter Estimation of Static/Dynamic Photovoltaic Models Using a Developed Version of Eagle Strategy Gradient-Based Optimizer
Sustainability 2021, 13(23), 13053; https://doi.org/10.3390/su132313053 - 25 Nov 2021
Viewed by 194
Abstract
The global trend towards renewable energy sources, especially solar energy, has had a significant impact on the development of scientific research to manufacture high-performance solar cells. The issue of creating a model that simulates a solar module and extracting its parameter is essential [...] Read more.
The global trend towards renewable energy sources, especially solar energy, has had a significant impact on the development of scientific research to manufacture high-performance solar cells. The issue of creating a model that simulates a solar module and extracting its parameter is essential in designing an improved and high performance photovoltaic system. However, the nonlinear nature of the photovoltaic cell increases the challenge in creating this model. The application of optimization algorithms to solve this issue is increased and developed rapidly. In this paper, a developed version of eagle strategy GBO with chaotic (ESCGBO) is proposed to enhance the original GBO performance and its search efficiency in solving difficult optimization problems such as this. In the literature, different PV models are presented, including static and dynamic PV models. Firstly, in order to evaluate the effectiveness of the proposed ESCGBO algorithm, it is executed on the 23 benchmark functions and the obtained results using the proposed algorithm are compared with that obtained using three well-known algorithms, including the original GBO algorithm, the equilibrium optimizer (EO) algorithm, and wild horse optimizer (WHO) algorithm. Furthermore, both of original GBO and developed ESCGBO are applied to estimate the parameters of single and double diode as static models, and integral and fractional models as examples for dynamic models. The results in all applications are evaluated and compared with different recent algorithms. The results analysis confirmed the efficiency, accuracy, and robustness of the proposed algorithm compared with the original one or the recent optimization algorithms. Full article
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