New Trends for Green Energy in Power Conversion System

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 8859

Special Issue Editors


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Guest Editor
Sharaf Energy Systems, Inc., Fredericton, NB E3C 2P2, Canada
Interests: electric utility-power systems; power electronics and electro-technology; FACTS; renewable and green energy systems; power quality; AI applications and environmental engineering systems

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Guest Editor
Electrical Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh 33516, Egypt
Interests: power system modeling, computation, and control; renewable energy; microgrids
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
1. Electrical Power and Machines Department, Faculty of Engineering, Zagazig University, Zagazig 44519, Egypt
2. Mechatronic Program, Faculty of Engineering and Technology Egyptian Chinese University, Cairo 45413122, Egypt
Interests: renewable energy integration techniques; energy conversion (solar-wind-wave energies) to electrical power generation; artificial intelligence applications in power systems, IoT, and hybrid cloud-based data processing for power system monitoring in smart and microgrids
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The energy sector faces an increased demand from various stakeholders to decrease the economic and technical performances of renewable energy resources through decreasing the cost of renewables while simultaneously improving the adoption rate of renewable energy. In recent decades, an increased penetration has been noticed, and therefore, their related technologies have experienced rapid improvements to meet the technoeconomic issues of power markets.

In this regard, this Special Issue aims to collect review and working articles from around the world which cover and illuminate the state of the art of development of renewable energy sources, energy conversion systems, and their recent technological spreads. Different types of renewable energy sources will be discussed, such as solar, wind, biomass, fuel cells, hydropower, hydrogen, nuclear, green energy, and geothermal.

Studies that comprehensively discuss each of these sources, associated materials, technological developments, economics, and impact on the environment are welcome. As renewable energy sources are intermittent, they require specific power electronic converters to convert the generated power into a useful form. Hence, this Special Issue will collect studies in the domain of power conversion  using different power converters, such as AC–DC, DC–DC, DC–AC, and AC–AC and concerned with the AC/DC grids. Further, advanced power semiconductor devices, their gate drive and protection circuits, heat sink design, and magnetic components for power converter are welcome topics.

The SI topics outlined above will have a large impact among colleagues from universities and academia in general, as well as scientists, policy makers, practitioners, and students in the fields of electronics and electrical power system engineering, energy engineering, automotive engineering, etc.

The scope of this SI is to cover recent developments in green energy and deal with the continuous technology advances in the domain of renewable energies and their penetration in electrical grids. The scope of this SI includes the following:

    1. Renewable energy resources;
    2. Smart grids and smart metering;
    3. Power quality problems with high RERs;
    4. Power electronic devices in energy conversion systems;
    5. Applications of the Internet of Energy;
    6. Power transmission technologies, including the development of FACTS devices;
    7. AC–DC grids;
    8. Optimal power flow;
    9. Reactive power resources;
    10. Energy storage devices;
    11. Batteries;
    12. Blockchain and deep learning methodologies;
    13. Energy as a Service;
    14. Distributed energy resources;
    15. Demand side management in smart grid environments;
    16. Quantum computing;
    17. Electric vehicles to grid;
    18. Power to X technologies;
    19. Green hydrogen fuels;
    20. Virtual power plants;
    21. Protection schemes of energy systems;
    22. Signal processing;
    23. Fault location in hybrid systems;
    24. Modeling of renewable energies based on optimization.

Prof. Dr. Adel M. Sharaf
Prof. Dr. Ragab A. El-Sehiemy
Prof. Dr. Mohamed Talaat
Guest Editors

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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. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • renewable energy resources
  • smart grid
  • green hydrogen technology
  • power electronic advances
  • technical and economic operation

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Published Papers (3 papers)

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Research

19 pages, 2405 KiB  
Article
An Active Distribution Grid Exceedance Testing and Risk-Planning Simulation Based on Carbon Capture and Multisource Data from the Power Internet of Things
by Jinghan Wu, Kun Wang, Tianhao Wang, Shiqian Ma, Hansen Gong, Zhijian Hu and Qingwu Gong
Electronics 2024, 13(8), 1413; https://doi.org/10.3390/electronics13081413 - 9 Apr 2024
Viewed by 891
Abstract
In order to achieve peak carbon and carbon neutrality targets, a high number of distributed power sources have been connected to distribution networks. How to realize the planning of a distribution network containing integrated energy under the condition of carbon capture and complete [...] Read more.
In order to achieve peak carbon and carbon neutrality targets, a high number of distributed power sources have been connected to distribution networks. How to realize the planning of a distribution network containing integrated energy under the condition of carbon capture and complete the exceedance test of the distribution network under the condition of accessing a large number of distributed generators has become an urgent problem. To solve the above problem while promoting sustainable development, this work proposes an active distribution network risk-planning model based on multisource data from carbon capture and the Power Internet of Things. The model calculates the semi-invariants of each order of the node state vectors and branch circuit current vectors and then utilizes Gram–Charlier-level expansion to obtain the exceeding probability density function and the probability distribution functions of the node voltages and line powers in the distribution network. Combined with multisource data, an active distribution network with an integrated energy system designed for carbon capture was modeled. According to the risk scenario of the distribution network, the nonconvex constraints in the model were simplified by second-order cone relaxation, and the optimal planning scheme of the distribution network was solved by combining the Gurobi solver with the risk index as the first-level objective and the economic benefit as the second-level objective. The simulation results of a coupled network consisting of a 39-node distribution network and an 11-node transportation network verified the effectiveness of the proposed model. Full article
(This article belongs to the Special Issue New Trends for Green Energy in Power Conversion System)
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27 pages, 10199 KiB  
Article
Dynamic Optimal Power Flow of Active Distribution Network Based on LSOCR and Its Application Scenarios
by Weiqi Meng, Dongran Song, Xiaofei Deng, Mi Dong, Jian Yang, Rizk M. Rizk-Allah and Václav Snášel
Electronics 2023, 12(7), 1530; https://doi.org/10.3390/electronics12071530 - 24 Mar 2023
Cited by 6 | Viewed by 2266
Abstract
Optimal power flow (OPF) is a crucial aspect of distribution network planning and operation. Conventional heuristic algorithms fail to meet the system requirements for speed and accuracy, while linearized OPF approaches are inadequate for distribution networks with high R/X ratios. To address these [...] Read more.
Optimal power flow (OPF) is a crucial aspect of distribution network planning and operation. Conventional heuristic algorithms fail to meet the system requirements for speed and accuracy, while linearized OPF approaches are inadequate for distribution networks with high R/X ratios. To address these issues and cater to multi-period scenarios, this study proposes a dynamic linearized second-order cone programming-based (SOCP) OPF model. The model is built by first establishing a dynamic OPF model based on linearized second-order conic relaxation (LSOCR-DOPF). The components of the active distribution network, such as renewable energy power generation units, energy storage units, on-load-tap-changers, static var compensators, and capacitor banks, are then separately modeled. The model is implemented in MATLAB and solved by YALMIP and GUROBI. Finally, three representative scenarios are used to evaluate the model accuracy and effectiveness. The results show that the proposed LSOCR-DOPF model can ensure calculation time within 3 min, voltage stability, and error control within 10−6 for all three applications. This method has strong practical value in the fields of active distribution network day-ahead dispatch, accurate modeling of ZIP load, and real-time operation. Full article
(This article belongs to the Special Issue New Trends for Green Energy in Power Conversion System)
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19 pages, 802 KiB  
Article
Decentralized Energy Management System in Microgrid Considering Uncertainty and Demand Response
by Sane Lei Lei Wynn, Terapong Boonraksa, Promphak Boonraksa, Watcharakorn Pinthurat and Boonruang Marungsri
Electronics 2023, 12(1), 237; https://doi.org/10.3390/electronics12010237 - 3 Jan 2023
Cited by 25 | Viewed by 4345
Abstract
Smart energy management and control systems can improve the efficient use of electricity and maintain the balance between supply and demand. This paper proposes the modeling of a decentralized energy management system (EMS) to reduce system operation costs under renewable generation and load [...] Read more.
Smart energy management and control systems can improve the efficient use of electricity and maintain the balance between supply and demand. This paper proposes the modeling of a decentralized energy management system (EMS) to reduce system operation costs under renewable generation and load uncertainties. There are three stages of the proposed strategy. First, this paper applies an autoregressive moving average (ARMA) model for forecasting PV and wind generations as well as power demand. Second, an optimal generation scheduling process is designed to minimize system operating costs. The well-known algorithm of particle swarm optimization (PSO) is applied to provide optimal generation scheduling among PV and WT generation systems, fuel-based generation units, and the required power from the main grid. Third, a demand response (DR) program is introduced to shift flexible load in the microgrid system to achieve an active management system. Simulation results demonstrate the performance of the proposed method using forecast data for hourly PV and WT generations and a load profile. The simulation results show that the optimal generation scheduling can minimize the operating cost under the worst-case uncertainty. The load-shifting demand response reduced peak load by 4.3% and filled the valley load by 5% in the microgrid system. The proposed optimal scheduling system provides the minimum total operation cost with a load-shifting demand response framework. Full article
(This article belongs to the Special Issue New Trends for Green Energy in Power Conversion System)
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