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Processes
Special Issues
Modeling and Operation of Renewable Energy System
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Modeling and Operation of Renewable Energy System

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (15 November 2022) | Viewed by 8473

Special Issue Editors

Prof. Dr. Osvaldo José Venturini

E-Mail Website
Guest Editor
Mechanical Engineering Institute, Federal University of Itajuba, 37500-903 Itajuba-MG, Brazil
Interests: alternative energy sources; mathematical modeling and optimization of thermal systems; hybrid biomass–solar systems; energy efficiency; thermal solar energy; LCA
Prof. Dr. Eduardo Silva Lora Electo

E-Mail Website
Guest Editor
Mechanical Engineering Institute, Federal University of Itajuba, Itajuba, MG 37500-903, Brazil
Interests: biomass combustion and gasification; renewable energy enhancement in the Brazilian electricity matrix; thermal solar energy modeling; biorefineries; LCA of bioenergy systems
Dr. Adriano Viana Ensinas

E-Mail Website
Guest Editor
Department of Engineering, Federal University of Lavras, Lavras, MG 37200-900, Brazil
Interests: biofuels; biomass conversion; process integration; modeling and design of biorefineries

Special Issue Information

Dear Colleagues,

The generation and use of renewable energy have become a priority of the global agendas for sustainability, since they can help to increase energy access, lower atmospheric emissions, and promote climate impact mitigation. In the coming years, energy conversion processes will face significant changes, creating opportunities for research, development, and investments. In this scenario, the development of models to represent the behavior of renewable energy generation and conversion systems becomes fundamental, as it contributes to mastering their design and operation techniques, allowing the comparison of different project alternatives, and control and operation strategies.

The purpose of this Special Edition of Processes is to present the latest methodological developments in the modeling of renewable energy systems, as well as to discuss results obtained during the operation of these systems, whether at the level of prototype demonstration or industrial applications. The topics to be covered include but are not limited to:

  • Optimal design and operation of hybrid solar–biomass power plants;
  • Resource availability modeling (solar, wind, wave, geothermal);
  • Assessment of biomass-based electricity generation systems;
  • Modeling, assessment, and operation of biorefineries;
  • Modeling of solar thermal and photovoltaic systems for design and operation;
  • Modeling and optimization of wind, wave, geothermal, and ocean systems;
  • Modeling of bio-SNG (synthetic natural gas) production;
  • Renewable hydrogen and power-to-X;
  • Assessment of maximum penetration of intermittent renewable energy sources with and without energy storage;
  • Multi-objective territorial planning of renewable energy source utilization;
  • Economic and environmental evaluation of renewable and hybrid systems.

Prof. Dr. Osvaldo José Venturini
Prof. Dr. Eduardo Silva Lora Electo
Dr. Adriano Viana Ensinas
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. Processes is an international peer-reviewed open access monthly 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

  • renewable energy
  • biomass
  • thermal solar energy
  • biorefineries
  • hybrid systems
  • modeling and optimization of energy systems
  • resource availability
  • renewable hydrogen
  • synthetic natural gas production

Published Papers (5 papers)

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Research

18 pages, 5549 KiB  
Article
Power Control Strategy for Hybrid System Using Three-Level Converters for an Insulated Micro-Grid System Application
by Moussa Gaptia Lawan, Mamadou Baïlo Camara, Abdulkareem Shaheed Sabr, Brayima Dakyo and Ahmed Al Ameri
Processes 2022, 10(12), 2539; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10122539 - 29 Nov 2022
Cited by 2 | Viewed by 1572
Abstract
This paper presents a simulation of an insulated micro-grid system based on the three-level converters control for energy management. Different renewable power sources (wind turbine and Photovoltaic (PV) energy systems) are used to energize the micro-grid. However, a battery energy storage system (BESS) [...] Read more.
This paper presents a simulation of an insulated micro-grid system based on the three-level converters control for energy management. Different renewable power sources (wind turbine and Photovoltaic (PV) energy systems) are used to energize the micro-grid. However, a battery energy storage system (BESS) and a variable diesel generator are also used to improve the reliability of the system. The contribution of this research is focused on the power control method based on improving the quality of energy transfer, mastering dynamic interactions and maximum energy production from renewable energies to reduce the fuel consumption by the diesel. Firstly, the proposed control model for each renewable energy was carried out through simulation in the environments of Matlab and Simulink to test the robustness and performance. The second part of this research is dedicated to managing the sharing of power between load, generators, and storage systems by extracting the references of power. The three-level PWM rectifiers for variable speed diesel generators was used to maintain and control the DC bus voltage of the isolated micro-grid. The results obtained from simulations show a good correlation between static and dynamic systems even for fluctuating sun power and wind speed. Full article
(This article belongs to the Special Issue Modeling and Operation of Renewable Energy System)
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22 pages, 5515 KiB  
Article
Energy and Economic Assessment of a System Integrated by a Biomass Downdraft Gasifier and a Gas Microturbine
by Nelson Calderon Henao, Osvaldo José Venturini, York Castillo Santiago, Electo Eduardo Silva Lora, Diego Mauricio Yepes Maya, Edson de Oliveira Pamplona, Jhon Steven Navarro Hoyos and Oswaldo Hideo Ando Junior
Processes 2022, 10(11), 2377; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10112377 - 12 Nov 2022
Cited by 2 | Viewed by 1433
Abstract
This work focuses on the energy and economic evaluation of a power generation system composed of a downdraft gasifier and gas microturbine. The gasification process was studied using wood pellets as fuel, while the influence of two gasification agents (air and oxygen-enriched air) [...] Read more.
This work focuses on the energy and economic evaluation of a power generation system composed of a downdraft gasifier and gas microturbine. The gasification process was studied using wood pellets as fuel, while the influence of two gasification agents (air and oxygen-enriched air) on parameters, such as low heating value (LHV), composition, and yield of syngas, were analyzed. The syngas produced from oxygen-enriched air gasification in a downdraft gasifier had an LHV higher than 8 MJ/Nm3, being suitable to be supplied in the gas microturbine. Subsequently, syngas use in the gas microturbine was evaluated, and the results demonstrated that microturbine efficiency dropped from 33.00% to 21.35%, while its power decreased from 200 kW to 81.35 kW. The power generation system was modeled using Aspen Plus® v 11.0 software and validated using results obtained from published experimental studies. Accordingly, the integrated generation system presented an overall efficiency of 11.82% for oxygen-enriched air gasification cases. On the other hand, an economic assessment through risk analysis using Monte Carlo simulations was performed using Crystal Ball® v11.1.2.4.850 software. The economic results indicated that the implementation of a generation system was economically unfeasible, however, if the electricity rate price was increased by 63%, the proposed configuration could be feasible. Full article
(This article belongs to the Special Issue Modeling and Operation of Renewable Energy System)
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26 pages, 3330 KiB  
Article
Stochastic Allocation of Photovoltaic Energy Resources in Distribution Systems Considering Uncertainties Using New Improved Meta-Heuristic Algorithm
by Abdulaziz Alanazi, Mohana Alanazi, Almoataz Y. Abdelaziz, Hossam Kotb, Ahmad H. Milyani and Abdullah Ahmed Azhari
Processes 2022, 10(11), 2179; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10112179 - 24 Oct 2022
Cited by 5 | Viewed by 1263
Abstract
In this paper, a stochastic-metaheuristic model is performed for multi-objective allocation of photovoltaic (PV) resources in 33-bus and 69-bus distribution systems to minimize power losses of the distribution system lines, improving the voltage profile and voltage stability of the distribution system buses, considering [...] Read more.
In this paper, a stochastic-metaheuristic model is performed for multi-objective allocation of photovoltaic (PV) resources in 33-bus and 69-bus distribution systems to minimize power losses of the distribution system lines, improving the voltage profile and voltage stability of the distribution system buses, considering the uncertainty of PV units’ power and network demand. The decision-making variables, including installation location and the size of PVs, are determined optimally via an improved human learning optimization algorithm (IHLOA). The conventional human learning optimization algorithm (IHLOA) is improved based on Gaussian mutation to enhance the exploration capability and avoid getting trapped in local optimal. The methodology is implemented in two cases as deterministic and stochastic without and with uncertainties, respectively. Monte Carol Simulation (MCS) based on probability distribution function (PDF) is used for uncertainties modeling. The deterministic results proved the superiority of the IHLOA compared with conventional HLOA, particle swarm optimization (PSO), to obtain better values of the different objectives and faster convergence speed and accuracy. The results are clear that enhancing the conventional HLOA has increased the algorithm’s ability to explore and achieve the optimal global solution with higher convergence accuracy. Moreover, the stochastic results were clear that considering the uncertainties leads to correct and robust decision-making against existing uncertainties and accurate knowledge of the network operator against the exact values of various objectives compared to the deterministic case. Full article
(This article belongs to the Special Issue Modeling and Operation of Renewable Energy System)
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17 pages, 3191 KiB  
Article
Renewable-Aware Geographical Load Balancing Using Option Pricing for Energy Cost Minimization in Data Centers
by Muhammad Imran Khan Khalil, Syed Adeel Ali Shah, Amer Taj, Muhammad Shiraz, Basem Alamri, Sadia Murawwat and Ghulam Hafeez
Processes 2022, 10(10), 1983; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10101983 - 01 Oct 2022
Cited by 4 | Viewed by 1325
Abstract
It is becoming increasingly difficult to properly control the power consumption of widely dispersed data centers. Energy consumption is high because of the need to run these data centers (DCs) that handle incoming user requests. The rising cost of electricity at the data [...] Read more.
It is becoming increasingly difficult to properly control the power consumption of widely dispersed data centers. Energy consumption is high because of the need to run these data centers (DCs) that handle incoming user requests. The rising cost of electricity at the data center is a contemporary problem for cloud service providers (CSPs). Recent studies show that geo-distributed data centers may share the load and save money using variable power prices and pricing derivatives in the wholesale electricity market. In this study, we evaluate the problem of reducing energy expenditures in geographically dispersed data centers while accounting for variable system dynamics, power price fluctuations, and renewable energy sources. We present a renewable energy-based load balancing employing an option pricing (RLB-Option) online algorithm based on a greedy approach for interactive task allocation to reduce energy costs. The basic idea of RLB-Option is to process incoming user requests using available renewable energy sources. In contrast, in the case of unprocessed user requests, the workload will be processed using brown energy or call option contract at each timeslot. We formulate the energy cost minimization in geo-distributed DCs as an optimization problem considering geographical load balancing, renewable energy, and an option pricing contract from the derivative market while satisfying the set of constraints. We prove that the RLB-Option can reduce the energy cost of the DCs close to that of the optimal offline algorithm with future information. Compared to standard workload allocation methods, RLB-Option shows considerable cost savings in experimental evaluations based on real-world data. Full article
(This article belongs to the Special Issue Modeling and Operation of Renewable Energy System)
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22 pages, 32649 KiB  
Article
Hydrodynamic and Morphodynamic Influences from Ocean Current Energy Conversion Sites in the South–Southeastern Brazilian Inner Shelf
by Eduardo de Paula Kirinus, Phelype Haron Oleinik and Wiliam Correa Marques
Processes 2022, 10(2), 340; https://0-doi-org.brum.beds.ac.uk/10.3390/pr10020340 - 10 Feb 2022
Viewed by 1699
Abstract
As marine renewable resources begin to become a feasible energy source, it becomes crucial to investigate the nearshore impact of hydrodynamic and morphodynamic processes. As part of the implementation of turbines in the numerical modeling environment of Telemac-3D and Sisyphe modules, we conducted [...] Read more.
As marine renewable resources begin to become a feasible energy source, it becomes crucial to investigate the nearshore impact of hydrodynamic and morphodynamic processes. As part of the implementation of turbines in the numerical modeling environment of Telemac-3D and Sisyphe modules, we conducted a 10-year run to evaluate nearshore impacts of turbines in the flow. We used five criteria to define viable locations. Turbines sites were added to a conversion energy model coupled into the hydrodynamic model in order to develop properly the flow changes towards the energy conversion process. The results revealed that in the three chosen spots, turbines were not converting equally the current energy within the site. In fact, the turbines located on the outer side of the farm developed greater conversion rates. This impacted the nearshore in the following ways: (1) the decrease in the currents intensity that generates strong adjustments in the water column, breaking the natural pattern of vertical circulation; (2) development of lateral flows that in time affects the bottom dynamics and results in changes in sediment deposition; and (3) increase in bedload transport rates around the turbine’s field due to divergence in the flow. The idealized turbines sites produced 1,775 GWh in 10 years, which could provide electricity to 54,181 residences during this period. Full article
(This article belongs to the Special Issue Modeling and Operation of Renewable Energy System)
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