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Modeling, Design, and Application of Hybrid Renewable Energy Systems

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 3263

Special Issue Editors


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Guest Editor
Departamento de Ingeniería Eléctrica, Universitat Politècnica de València, Valencia, Spain
Interests: microgrids; smart grids; renewable sources; PV systems; biomass gasification systems for power generation; wind systems; storage systems; microgrid simulation; hybrid systems based on renewables; microgrid control
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Guest Editor
Instituto de Ingeniería Energética, Universitat Politècnica de València, Valencia, Spain
Interests: Renewable sources, PV systems, biomass gasification systems for power generation, Wind systems, storage systems, Microgrid simulation, Hybrid systems based on renewables

Special Issue Information

Dear Colleagues,

Hybrid renewable energy systems (HRES) are gaining importance in modern power generation systems as a sustainable and cost-effective solution for distributed generation sources and self-consumption. As the share of renewable energy in the overall energy mix continues to increase, HRES offers a practical solution to balance power supply and demand, reduce transmission and distribution systems losses, and provide a stable grid. This Special Issue seeks to advance the field of HRES by encouraging original and novel contributions aimed at improving the sustainability, efficiency, reliability, flexibility, and profitability of HRES. Researchers working on microgrids are invited to contribute to this Special Issue, which focuses on the following topics:

  • Sustainable power generation systems through renewable energy sources (PV, wind, biomass, water, among others);
  • Storage systems (lead-acid batteries, Li-ion batteries, and others);
  • HRES power electronics;
  • HRES design;
  • Off-grid and grid-tied HRES;
  • Metaheuristic algorithms and methods applied to HRES (e.g., Artificial Neural Networks, Fuzzy Logic, Nature and Bio-inspired Optimization Algorithms, and others);
  • HRES economic analysis;
  • Energy Prosumers;
  • HRES demand response;
  • Power generation in developing countries through HRES.

An environmental and economic analysis is essential to evaluate the alternatives and choose the best option. By integrating the different components of HRES, a sustainable, efficient, reliable, flexible, and profitable renewable energy system can be achieved, contributing to a greener and more sustainable future.

Prof. Dr. Carlos Vargas-Salgado
Dr. David Alfonso-Solar
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

  • PV systems
  • wind systems
  • storage systems
  • microgrids
  • smartgrids
  • biomass gasification systems
  • hydropower systems
  • power control
  • greenhouse gas emissions
  • emissions
  • reliability of the grid
  • lithium-ion batteries
  • lead-acid batteries in microgrids
  • demand response
  • SCADA
  • control algorithms
  • energy management systems
  • microgrid simulation
  • power electronics
  • losses in power systems
  • hybrid energy systems
  • virtual power plants
  • prosumer
  • distributed energy resources (DER)
  • hybrid renewable energy System economic analysis
  • hybrid renewable energy systems for developing countries
  • metaheuristic algorithms
  • fuzzy logic
  • bio-inspired optimization
  • optimization algorithms
  • grey wolf optimizer (GWO) algorithm
  • particle swarm optimization (PSO) algorithm
  • genetic algorithms.

Published Papers (3 papers)

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Research

15 pages, 6031 KiB  
Article
Comparative Analysis of Hybrid Maximum Power Point Tracking Algorithms Using Voltage Scanning and Perturb and Observe Methods for Photovoltaic Systems under Partial Shading Conditions
by Musa Yilmaz
Sustainability 2024, 16(10), 4199; https://doi.org/10.3390/su16104199 - 16 May 2024
Viewed by 318
Abstract
Partial shading significantly affects the performance of photovoltaic (PV) power systems, rendering traditional maximum power point tracking (MPPT) methods ineffective. This study proposes a novel hybrid MPPT algorithm integrating voltage scanning and modified Perturb and Observe (P&O) techniques to overcome the limitations posed [...] Read more.
Partial shading significantly affects the performance of photovoltaic (PV) power systems, rendering traditional maximum power point tracking (MPPT) methods ineffective. This study proposes a novel hybrid MPPT algorithm integrating voltage scanning and modified Perturb and Observe (P&O) techniques to overcome the limitations posed by partial shading. This algorithm has a simple structure and does not require panel information such as the number of panels or voltage due to its voltage scanning feature. To test the proposed algorithm, a grid-connected PV power system with a power of 252.6 kW was created in the MATLAB/Simulink environment. In this power system, six different PS conditions, containing quite challenging situations, were listed in three different scenarios and simulated. The proposed algorithm was compared with the voltage scanning and P&O and voltage scanning and variable-step P&O methods. It was observed that the proposed algorithm has lower power fluctuations compared to the other two traditional methods. Additionally, this algorithm managed to achieve higher efficiency than the other methods in some cases. Full article
(This article belongs to the Special Issue Modeling, Design, and Application of Hybrid Renewable Energy Systems)
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40 pages, 7056 KiB  
Article
Performance and Techno-Economic Analysis of Optimal Hybrid Renewable Energy Systems for the Mining Industry in South Africa
by Mpho Sam Nkambule, Ali N. Hasan and Thokozani Shongwe
Sustainability 2023, 15(24), 16766; https://doi.org/10.3390/su152416766 - 12 Dec 2023
Cited by 1 | Viewed by 1286
Abstract
This paper presents an exploration of the potential of hybrid renewable energy systems (HRESs), combining floating solar photovoltaics (FPV), wind turbines, and vanadium redox flow (VRF) battery energy storage systems (BESSs) to expedite the transition from conventional to renewable energy for the mining [...] Read more.
This paper presents an exploration of the potential of hybrid renewable energy systems (HRESs), combining floating solar photovoltaics (FPV), wind turbines, and vanadium redox flow (VRF) battery energy storage systems (BESSs) to expedite the transition from conventional to renewable energy for the mining sector in South Africa. The feasibility study assesses how to enhance the overall efficiency and minimize greenhouse gas emissions from an economic standpoint by using the Hybrid Optimization of Multiple Energy Resources (HOMER) grid software version 1.11.1 and PVsyst version 7.4. Furthermore, the BESS Covariance Matrix Adaptation Evolution Strategy (CMA-ES) dispatch algorithm is proposed to make the most of the battery storage capacity and capability, aligning it with the dynamic energy demand and supply patterns of an HRES. The proposed HRES includes a highly efficient SFPV with a performance ratio of 0.855 and an annual energy production of 15,835 MWh; a wind turbine (WT) operating for 2977 h annually, achieving a 25% wind penetration rate; and a dynamic VRF-BESS with a 15,439 kWh life throughput and a 3 s dispatch response time. This HRES has a CapEx of R172 million, a 23.5% Internal Rate of Return (IRR), and an investment payback period of 4.9 years. It offers a low Levelized Cost of Energy (LCoE) at 4.27 R/kWh, a competitive Blended Cost of Energy (BCoE) at 1.91 R/kWh, and a positive net present cost (NPC), making it economically advantageous without external subsidies. Moreover, it annually reduces CO2 emissions by 1,715,468 kg, SO2 emissions by 7437 kg, and NOx emissions by 3637 kg, contributing to a significant environmental benefit. Full article
(This article belongs to the Special Issue Modeling, Design, and Application of Hybrid Renewable Energy Systems)
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25 pages, 12290 KiB  
Article
Optimum Generated Power for a Hybrid DG/PV/Battery Radial Network Using Meta-Heuristic Algorithms Based DG Allocation
by Mohamed Els. S. Abdelwareth, Dedet Candra Riawan and Chow Chompoo-inwai
Sustainability 2023, 15(13), 10680; https://doi.org/10.3390/su151310680 - 6 Jul 2023
Viewed by 1172
Abstract
This paper presents four optimization outcomes for a diesel generator (DG), photovoltaic (PV), and battery hybrid generating radial system, to reduce the network losses and achieve optimum generated power with minimum costs. The effectiveness of the four utilized meta-heuristic algorithms in this paper [...] Read more.
This paper presents four optimization outcomes for a diesel generator (DG), photovoltaic (PV), and battery hybrid generating radial system, to reduce the network losses and achieve optimum generated power with minimum costs. The effectiveness of the four utilized meta-heuristic algorithms in this paper (firefly algorithm, particle swarm optimization, genetic algorithm, and surrogate optimization) was compared, considering factors such as Cost of Energy (COE), the Loss of Power Supply Probability (LPSP), and the coefficient of determination (R2). The multi-objective function approach was adopted to find the optimal DG allocation sizing and location using the four utilized algorithms separately to achieve the optimal solution. The forward-backward sweep method (FBSM) was employed in this research to compute the network’s power flow. Based on the computed outcomes of the algorithms, the inclusion of an additional 300 kW DG in bus 2 was concluded to be an effective strategy for optimizing the system, resulting in maximizing the generated power with minimum network losses and costs. Results reveal that DG allocation using the firefly algorithm outperforms the other three algorithms, reducing the burden on the main DG and batteries by 30.48% and 19.24%, respectively. This research presents an optimization of an existing electricity network case study located on Tomia Island, Southeast Sulawesi, Indonesia. Full article
(This article belongs to the Special Issue Modeling, Design, and Application of Hybrid Renewable Energy Systems)
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