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Modern Energy Storage Technologies towards Decarbonized Power Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D: Energy Storage and Application".

Deadline for manuscript submissions: 25 July 2024 | Viewed by 4609

Special Issue Editors


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Guest Editor
1. Department of Electrical Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates
2. Department of Electrical Engineering, South Valley University, Qena 83523, Egypt
Interests: power systems; renewable energy sources; microgrids; smart grid; electric vehicles; energy storage systems; optimization

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Guest Editor
Department of Electrical Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates
Interests: reliability and security of the power systems; energy management systems; microgrids; smart grids; planning and operation of renewable resources; electric vehicles and storage systems
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
1. Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland
2. Department of Electrical Engineering, Aswan University, Aswan 81542, Egypt
Interests: power systems; energy storage; electrical vehicles; renewable energy; smart grids; applied machine learning
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Electrical and Computer Engineering, Florida International University, Miami, FL 33174, USA
Interests: smart grid; metaheuristics applications in power systems; computational intelligence; cyberphysical systems; transportation electrification
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recently, countries have been moving towards the massive integration of renewable energy sources (RES) due to their environmental-based role in carbon-free electricity supply. However, the high penetration of these sources (such as photovoltaics and wind turbines) and the intermittency and uncertainty associated with the output power of such energy sources have brought new operational and technical challenges to electrical power systems. As a result, the importance of modern energy storage technologies (EST), as promising solutions for achieving the power system’s required performance, has become critical. Modern ESTs are defined as practical and effective approaches for stabilizing the power supply to overcome such challenges and minimize energy peak demands. Moreover, they can mitigate power fluctuations due to the intermittent nature of RES. Further, EST effectively reduces system imbalances, adopts load shifting and reserves, and decreases operation costs in the system. This Special Issue focuses on the application of modern energy storage technologies in forthcoming power systems. Specifically, it covers the recent advancement in the application of different types of energy storage facilities, such as batteries, heat buffer tanks, fuel cells, compressed air energy storage systems, hydrogen energy storage, and electric vehicles as means of energy storage in smart grids. The targeted research topics include, but are not limited to:

  • Optimal allocation of modern EST in power systems;
  • Hydrogen production and storage;
  • Coordinated operation and control of RES and EST-assisted hybrid power systems;
  • Different bidding strategies of storage technologies;
  • Virtual inertia emulation using EST;
  • Reliability and uncertainty analysis of EST;
  • Thermal management of EST;
  • Multi-energy storage systems in smart grids.

Dr. Abdelfatah Ali
Dr. Mostafa Shaaban
Dr. Karar Mahmoud
Prof. Dr. Osama A. Mohammed
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. Energies 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 2600 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

  • energy storage
  • renewable energy sources
  • electric vehicles
  • power systems
  • smart grid
  • hybrid power system
  • energy management

Published Papers (3 papers)

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Research

23 pages, 6068 KiB  
Article
Research on the Performance Improvement Method for Lithium-Ion Battery in High-Power Application Scenarios
by Pengfei Zhou, Liying Zhu, Dawei Fu, Jianguo Du, Xinze Zhao and Bingxiang Sun
Energies 2024, 17(7), 1746; https://0-doi-org.brum.beds.ac.uk/10.3390/en17071746 - 05 Apr 2024
Viewed by 569
Abstract
With the development of technology, high-power lithium-ion batteries are increasingly moving towards high-speed discharge, long-term continuous output, instantaneous high-rate discharge, and miniaturization, and are being gradually developed towards the fields of electric tools, port machinery and robotics. Improving the power performance of batteries [...] Read more.
With the development of technology, high-power lithium-ion batteries are increasingly moving towards high-speed discharge, long-term continuous output, instantaneous high-rate discharge, and miniaturization, and are being gradually developed towards the fields of electric tools, port machinery and robotics. Improving the power performance of batteries can be achieved from multiple dimensions, such as electrochemical systems and battery design. In order to improve the power performance of lithium-ion batteries, this paper proposes design methods from the perspective of electrochemical systems, which include increasing the high-rate discharge capacity and low impedance of the battery. This article also studies the preparation of high-power lithium-ion batteries. This article aims to improve the rate performance of batteries by studying high-performance cathode materials, excellent conductive networks, and high-performance electrolytes. This article successfully screened high-performance cathode materials by comparing the effects of different particle sizes of cathode materials on electrode conductivity and battery internal resistance. By comparing the effects of electrolyte additives under pulse cycling, high-quality electrolyte additive materials were selected. By comparing the effects of different types, contents, and ratios of conductive agents on electrode conductivity, battery internal resistance, high-quality conductive agents, and appropriate ratios were selected. Finally, a 10 Ah cylindrical high-power lithium-ion battery with a specific energy of 110 Wh/kg, pulse discharge specific power of 11.3 kW/kg, an AC internal resistance of ≤0.7 m Ω, a 10C full capacity discharge cycle of over 1700, a 30C full capacity discharge cycle of over 500, and a continuous discharge capacity of 10C–30C, and a pulse discharge capacity of over 100C was prepared. Full article
(This article belongs to the Special Issue Modern Energy Storage Technologies towards Decarbonized Power Systems)
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18 pages, 6926 KiB  
Article
Enhancement of Microgrid Frequency Stability Based on the Combined Power-to-Hydrogen-to-Power Technology under High Penetration Renewable Units
by Abdel-Raheem Youssef, Mohamad Mallah, Abdelfatah Ali, Mostafa F. Shaaban and Essam E. M. Mohamed
Energies 2023, 16(8), 3377; https://0-doi-org.brum.beds.ac.uk/10.3390/en16083377 - 12 Apr 2023
Cited by 8 | Viewed by 1628
Abstract
Recently, with the large-scale integration of renewable energy sources into microgrid (μGs) power electronics, distributed energy systems have gained popularity. However, low inertia reduces system frequency stability and anti-disturbance capabilities, exposing power quality to intermittency and uncertainty in photovoltaics or [...] Read more.
Recently, with the large-scale integration of renewable energy sources into microgrid (μGs) power electronics, distributed energy systems have gained popularity. However, low inertia reduces system frequency stability and anti-disturbance capabilities, exposing power quality to intermittency and uncertainty in photovoltaics or wind turbines. To ensure system stability, the virtual inertia control (VIC) is presented. This paper proposes two solutions to overcome the low inertia problem and the surplus in capacities resulting from renewable energy sources. The first solution employs superconducting magnetic energy storage (SMES), which can be deemed as an efficient solution for damping the frequency oscillations. Therefore, in this work, SMES that is managed by a simple proportional-integral-derivative controller (PID) controller is utilized to overcome the low inertia. In the second solution, the hydrogen storage system is employed to maintain the stability of the microgrid by storing surplus power generated by renewable energy sources (RESs). Power-to-Power is a method of storing excess renewable energy as chemical energy in the form of hydrogen. Hydrogen can be utilized locally or delivered to a consumption node. The proposed μG operation demonstrates that the integration of the photovoltaics (PVs), wind turbines (WTs), diesel engine generator (DEG), electrolyzer, micro gas turbine (μGT), and SMES is adequate to fulfill the load requirements under transient operating circumstances such as a low and high PV output power as well as to adapt to sudden changes in the load demand. The effectiveness of the proposed schemes is confirmed using real irradiance data (Benban City, Egypt) using a MATLAB/SIMULINK environment. Full article
(This article belongs to the Special Issue Modern Energy Storage Technologies towards Decarbonized Power Systems)
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13 pages, 4029 KiB  
Article
Real-Time Pricing-Enabled Demand Response Using Long Short-Time Memory Deep Learning
by Aftab Ahmed Almani and Xueshan Han
Energies 2023, 16(5), 2410; https://0-doi-org.brum.beds.ac.uk/10.3390/en16052410 - 02 Mar 2023
Cited by 3 | Viewed by 1371
Abstract
Sustainable energy development requires environment-friendly energy-generating methods. Pricing system constraints influence the efficient use of energy resources. Real-Time Pricing (RTP) is theoretically superior to previous pricing systems for allowing demand response (DR) activities. The DR approach has been useful for correcting supply–demand imbalances [...] Read more.
Sustainable energy development requires environment-friendly energy-generating methods. Pricing system constraints influence the efficient use of energy resources. Real-Time Pricing (RTP) is theoretically superior to previous pricing systems for allowing demand response (DR) activities. The DR approach has been useful for correcting supply–demand imbalances as technology has evolved. There are several systems for determining and controlling the DR. However, most of these solutions are unable to control rising demand or forecast prices for future time slots. This research provides a Real-Time Pricing DR model for energy management based on deep learning, where the learning framework is trained on demand response and real-time pricing. The study data in this article were taken from the Australian Energy Market Operator (AEMO), and the learning framework was trained over 17 years of data to forecast the real future energy price and demand. To investigate the suggested deep learning-based dynamic pricing strategy, two prediction instances are addressed: actual–predicted demand and actual–predicted price. We estimated pricing and demand outcomes using long short-term memory (LSTM), which were then greatly improved by architectural changes in the model. The findings showed that the suggested model is suitable for energy management in terms of demand and price prediction. Full article
(This article belongs to the Special Issue Modern Energy Storage Technologies towards Decarbonized Power Systems)
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