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Keywords = flywheel energy storage system

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18 pages, 9706 KiB  
Article
Dynamics Study of Hybrid Support Flywheel Energy Storage System with Damping Ring Device
by Mingming Hu, Kun Liu, Jingbo Wei, Eryong Hou, Duhe Liu and Xi Zhao
Actuators 2024, 13(12), 532; https://doi.org/10.3390/act13120532 - 23 Dec 2024
Abstract
The flywheel energy storage system (FESS) of a mechanical bearing is utilized in electric vehicles, railways, power grid frequency modulation, due to its high instantaneous power and fast response. However, the lifetime of FESS is limited because of significant frictional losses in mechanical [...] Read more.
The flywheel energy storage system (FESS) of a mechanical bearing is utilized in electric vehicles, railways, power grid frequency modulation, due to its high instantaneous power and fast response. However, the lifetime of FESS is limited because of significant frictional losses in mechanical bearings and challenges associated with passing the critical speed. To suppress the unbalanced response of FESS at critical speed, a damping ring (DR) device is designed for a hybrid supported FESS with mechanical bearing and axial active magnetic bearing (AMB). Initially, the dynamic model of the FESS with DR is established using Lagrange’s equation. Moreover, the dynamic parameters of the DR are obtained by experimental measurements using the method of free vibration attenuation. Finally, the influence of the DR device on the critical speed and unbalanced response of FESS is analyzed. The results show that the designed DR device can effectively reduce the critical speed of FESS, and increase the first and second mode damping ratio. The critical speed is reduced from 13,860 rpm to 5280 rpm. Compared with FESS of the mechanical bearing, the unbalanced response amplitude of the FESS with DR is reduced by more than 87.8%, offering promising technical support for the design of active and passive control systems in FESS. Full article
(This article belongs to the Special Issue Actuator Technology for Active Noise and Vibration Control)
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<p>Schematic of FESS structure.</p>
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<p>Simplified model of FESS rotor–bearing system.</p>
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<p>FESS.</p>
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<p>Unfilled DR.</p>
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<p>Cross-section of the DR measuring device.</p>
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<p>Experimental procedure of DR.</p>
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<p>Experimental platform of DR.</p>
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<p>Curve fitting of free decay data.</p>
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<p>Modal shapes of FESS with DR at 0 rpm: (<b>a</b>) first modal, (<b>b</b>) second modal, (<b>c</b>) third modal, (<b>d</b>) fourth modal.</p>
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<p>Modal shapes of FESS with DR at 12,000 rpm: (<b>a</b>) first modal, (<b>b</b>) second modal, (<b>c</b>) third modal, (<b>d</b>) fourth modal.</p>
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<p>Variation of 1st- to 4th-order modal damping ratio with damping coefficients: (<b>a</b>) <math display="inline"><semantics> <msub> <mi>c</mi> <mn>1</mn> </msub> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <msub> <mi>c</mi> <mn>4</mn> </msub> </semantics></math>.</p>
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<p>Campbell diagram of the FESS: (<b>a</b>) REB + DR, (<b>b</b>) REB.</p>
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<p>Variation of unbalanced response with stiffness: (<b>a</b>) upper bearing, (<b>b</b>) upper end face of flywheel.</p>
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<p>Variation of unbalanced response with damping: (<b>a</b>) upper bearing, (<b>b</b>) upper end face of flywheel.</p>
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<p>Comparison of unbalanced response: (<b>a</b>) upper bearing, (<b>b</b>) upper flywheel end face, (<b>c</b>) lower flywheel end face, (<b>d</b>) lower bearing.</p>
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15 pages, 8380 KiB  
Article
Design and Analysis of a Low Torque Ripple Permanent Magnet Synchronous Machine for Flywheel Energy Storage Systems
by Yubo Sun, Zhenghui Zhao and Qian Zhang
Energies 2024, 17(24), 6337; https://doi.org/10.3390/en17246337 - 16 Dec 2024
Viewed by 381
Abstract
Flywheel energy storage systems (FESS) are technologies that use a rotating flywheel to store and release energy. Permanent magnet synchronous machines (PMSMs) are commonly used in FESS due to their high torque and power densities. One of the critical requirements for PMSMs in [...] Read more.
Flywheel energy storage systems (FESS) are technologies that use a rotating flywheel to store and release energy. Permanent magnet synchronous machines (PMSMs) are commonly used in FESS due to their high torque and power densities. One of the critical requirements for PMSMs in FESS is low torque ripple. Therefore, a PMSM with eccentric permanent magnets is proposed and analyzed in this article to reduce torque ripple. Cogging torque, a significant contributor to torque ripple, is investigated by a combination of finite element analysis and the analytical method. An integer-slot distribution winding structure is adopted to reduce vibration and noise. Moreover, the effects of eccentric permanent magnets and harmonic injection on the cogging torque are analyzed and compared. In addition, the electromagnetic performance is analyzed, and the torque ripple is found to be 3.1%. Finally, a prototype is built and tested, yielding a torque ripple of 3.9%, to verify the theoretical analysis. Full article
(This article belongs to the Special Issue Energy, Electrical and Power Engineering: 3rd Edition)
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<p>Topology of proposed PMSM.</p>
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<p>Winding connection.</p>
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<p>Analysis model of surface-mounted PMSM.</p>
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<p>Bread-type eccentric permanent magnet.</p>
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<p>Influence of eccentricity on torque performance.</p>
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<p>Cogging torque of PMSM with different permanent magnets.</p>
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<p>Air gap magnetic densities of PMSM with different permanent magnets. (<b>a</b>) Radial air gap magnetic densities. (<b>b</b>) Tangential air gap magnetic densities. (<b>c</b>) Harmonic order.</p>
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<p>Cogging torque contribution of different harmonics. (<b>a</b>) PMSM with original permanent magnets. (<b>b</b>) PMSM with eccentric permanent magnets.</p>
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<p>Permanent magnet with third harmonic injection.</p>
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<p>Cogging torque of PMSM with harmonic injection. (<b>a</b>) Effect of harmonic injection. (<b>b</b>) Contribution of harmonics.</p>
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<p>Load electromagnetic performance. (<b>a</b>) Magnetic field line. (<b>b</b>) Magnetic flux density.</p>
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<p>Back electromotive force of PMSM.</p>
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<p>Torque performance of PMSM. (<b>a</b>) Cogging torque. (<b>b</b>) Torque.</p>
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<p>Vibration acceleration of PMSM with different permanent magnets.</p>
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<p>Prototype.</p>
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<p>Experimental platform.</p>
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<p>Vibration and noise test platform.</p>
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<p>Comparison of experimental and simulated results. (<b>a</b>) Back electromotive force of prototype. (<b>b</b>) Comparison of back electromotive force coefficient.</p>
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<p>Experimental results. (<b>a</b>) Torque. (<b>b</b>) Vibration acceleration.</p>
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20 pages, 4322 KiB  
Article
Research on Energy Management Technology of Photovoltaic-FESS-EV Load Microgrid System
by Yahong Xing, Wenping Qin, Haixiao Zhu, Kai Liu and Chengpeng Zhou
World Electr. Veh. J. 2024, 15(11), 508; https://doi.org/10.3390/wevj15110508 - 6 Nov 2024
Viewed by 571
Abstract
This study focuses on the development and implementation of coordinated control and energy management strategies for a photovoltaic–flywheel energy storage system (PV-FESS)-electric vehicle (EV) load microgrid with direct current (DC). A comprehensive PV-FESS microgrid system is constructed, comprising PV power generation, a flywheel [...] Read more.
This study focuses on the development and implementation of coordinated control and energy management strategies for a photovoltaic–flywheel energy storage system (PV-FESS)-electric vehicle (EV) load microgrid with direct current (DC). A comprehensive PV-FESS microgrid system is constructed, comprising PV power generation, a flywheel energy storage array, and electric vehicle loads. The research delves into the control strategies for each subsystem within the microgrid, investigating both steady-state operations and transitions between different states. A novel energy management strategy, centered on event-driven mode switching, is proposed to ensure the coordinated control and stable operation of the entire system. Based on the simulation results, the PV system cannot cope with the load demand power when it is increased to a maximum of 2800 W, the effectiveness of the individual control strategies, the coordinated control of the subsystems, and the overall energy management approach are confirmed. The main contribution of this research is the development of a coordinated control mechanism that integrates PV generation with FESS and EV loads, ensuring synchronized operation and enhanced stability of the microgrid. This work provides significant insights into optimizing energy distribution and minimizing losses within microgrid systems, thereby advancing the field of energy management in DC microgrids. Full article
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<p>Coordinate transformation of the PMSM.</p>
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<p>The control strategy of the grid PWM converter.</p>
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<p>The control strategy of the PV unit.</p>
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<p>Structure of the FESS units.</p>
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<p>The control strategy of the FESS units in the charging mode.</p>
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<p>The control strategy of the FESS units in discharging mode in mode 1.</p>
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<p>The control strategy of the FESS units in discharging mode in mode 2.</p>
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<p>Comparison of load requirement and PV supply in one day.</p>
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<p>Energy management state diagram.</p>
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<p>Energy management flow chart.</p>
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<p>Model of the DC grid in MATLAB.</p>
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<p>Energy management strategy of the FESS units in charging mode.</p>
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<p>Energy management strategy of the FESS units in charging mode.</p>
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<p>Energy management strategy of the FESS units in discharging mode.</p>
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<p>Energy management strategy of the FESS units in discharging mode.</p>
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25 pages, 3366 KiB  
Review
An Overview of the R&D of Flywheel Energy Storage Technologies in China
by Xingjian Dai, Xiaoting Ma, Dongxu Hu, Jibing Duan and Haisheng Chen
Energies 2024, 17(22), 5531; https://doi.org/10.3390/en17225531 - 5 Nov 2024
Viewed by 857
Abstract
The literature written in Chinese mainly and in English with a small amount is reviewed to obtain the overall status of flywheel energy storage technologies in China. The theoretical exploration of flywheel energy storage (FES) started in the 1980s in China. The experimental [...] Read more.
The literature written in Chinese mainly and in English with a small amount is reviewed to obtain the overall status of flywheel energy storage technologies in China. The theoretical exploration of flywheel energy storage (FES) started in the 1980s in China. The experimental FES system and its components, such as the flywheel, motor/generator, bearing, and power electronic devices, were researched around thirty years ago. About twenty organizations devote themselves to the R&D of FES technology, which is developing from theoretical and laboratory research to the stage of engineering demonstration and commercial application. After the research and accumulation in the past 30 years, the initial FES products were developed by some companies around 10 years ago. Today, the overall technical level of China’s flywheel energy storage is no longer lagging behind that of Western advanced countries that started FES R&D in the 1970s. The reported maximum tip speed of the new 2D woven fabric composite flywheel arrived at 900 m/s in the spin test. A steel alloy flywheel with an energy storage capacity of 125 kWh and a composite flywheel with an energy storage capacity of 10 kWh have been successfully developed. Permanent magnet (PM) motors with power of 250–1000 kW were designed, manufactured, and tested in many FES assemblies. The lower loss is carried out through innovative stator and rotor configuration, optimizing magnetic flux and winding arrangement for harmonic magnetic field suppression. Permanent magnetic bearings with high load ability up to 50–100 kN were developed both for a 1000 kW/16.7 kWh flywheel used for the drilling practice application in hybrid power of an oil well drilling rig and for 630 kW/125 kWh flywheels used in the 22 MW flywheel array applied to the flywheel and thermal power joint frequency modulation demonstration project. It is expected that the FES demonstration application power stations with a total cumulative capacity of 300 MW will be built in the next five years. Full article
(This article belongs to the Special Issue Flywheel Energy Storage Systems and Applications Ⅱ)
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<p>Configuration of flywheel energy storage system.</p>
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<p>Six kinds of flywheel: (<b>a</b>) 1000 kWh flywheel concept design; (<b>b</b>) 200 Wh winding composite AMB flywheel; (<b>c</b>) woven fabric composite flywheel; (<b>d</b>) magnet element embedded fiber spoke flywheel; (<b>e</b>) 10 kWh composite flywheel (Tsinghua Univ.); and (<b>f</b>) 90 kWh steel flywheel (IET, CAS).</p>
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<p>A new type of M/G and flywheel. (<b>a</b>) The 3D model of the flywheel and M/G. (<b>b</b>) The profile view of the M/G.</p>
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<p>A 50–100 kN permanent magnetic bearing stator. (<b>a</b>) Permanent ring with sector blocks. (<b>b</b>) Halbach array magnetic ring.</p>
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<p>Charging and discharging principles of motor-power electronic system: (<b>a</b>) charging and (<b>b</b>) discharging.</p>
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<p>Charging and discharging principles of motor-power electronic system: (<b>a</b>) charging and (<b>b</b>) discharging.</p>
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<p>Integration flywheel energy storage system.</p>
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<p>Flywheel energy storage unit and array built in China: (<b>a</b>) 500 kw/50 kWh FESU, 2023, and (<b>b</b>) 20 MW Flywheels Array, 2023.</p>
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<p>Simulink model of the control of FES and wind power system.</p>
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<p>FES application in PV power.</p>
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<p>Potential energy regenerating and load leveling of oil drilling rig.</p>
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15 pages, 3474 KiB  
Article
Application of Discrete Variable-Gain-Based Self-Immunity Control to Flywheel Energy Storage Systems
by Jian Sun, Pengju Yin and Xiangliu Song
Energies 2024, 17(21), 5373; https://doi.org/10.3390/en17215373 - 29 Oct 2024
Viewed by 484
Abstract
For the study of the trade-off between steady-state error and transient response in control systems for flywheel energy storage, a controller with a discrete variable gain is proposed. This controller aims to adapt to changes in the system state by dynamically adjusting the [...] Read more.
For the study of the trade-off between steady-state error and transient response in control systems for flywheel energy storage, a controller with a discrete variable gain is proposed. This controller aims to adapt to changes in the system state by dynamically adjusting the controller gain to optimize the system’s anti-disturbance performance. Theoretical analysis and mathematical derivation demonstrate that increasing the observer gain can significantly enhance the system’s anti-disturbance capability. However, this increase also results in overshooting, which highlights the limitations of traditional control methods in achieving both system stability and anti-disturbance performance. A discrete variable-gain extended state observer is designed. The gain of this observer can be adaptively adjusted according to a system state value, enabling the effective control of both steady-state error and transient response. Additionally, the stability of the proposed control method was analyzed and verified, ensuring its effectiveness and reliability for practical applications. Finally, the effectiveness of the proposed method in improving system performance is demonstrated by simulation results. Full article
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<p>Topology diagram of the main circuit of the FESS.</p>
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<p>LADRC-based system.</p>
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<p>(<b>a</b>) Bode diagram of the ratio of the output signal <math display="inline"><semantics> <mrow> <mi>u</mi> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math> to the input signal <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>1</mn> </msub> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math>, which mainly reflects the relationship between them; (<b>b</b>) Bode diagram of the ratio of the input signal <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>1</mn> </msub> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math> to the perturbation signal <math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mn>3</mn> </msub> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math>, which mainly reflects the relationship between them.</p>
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<p>Busbar voltage comparison chart (12,000 r/min).</p>
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<p>Flywheel oscillation comparison chart (12,000 r/min).</p>
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<p>Busbar voltage comparison chart (9000 r/min).</p>
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<p>Flywheel oscillation comparison chart (9000 r/min).</p>
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<p>A comparison plot of bus voltage at 12,000 r/min for various control strategies.</p>
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<p>Comparison of flywheel pendulum oscillations under different control strategies at 12,000 r/min.</p>
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25 pages, 3319 KiB  
Review
Grid Integration of Offshore Wind Energy: A Review on Fault Ride Through Techniques for MMC-HVDC Systems
by Dileep Kumar, Wajiha Shireen and Nanik Ram
Energies 2024, 17(21), 5308; https://doi.org/10.3390/en17215308 - 25 Oct 2024
Viewed by 961
Abstract
Over the past few decades, wind energy has expanded to become a widespread, clean, and sustainable energy source. However, integrating offshore wind energy with the onshore AC grids presents many stability and control challenges that hinder the reliability and resilience of AC grids, [...] Read more.
Over the past few decades, wind energy has expanded to become a widespread, clean, and sustainable energy source. However, integrating offshore wind energy with the onshore AC grids presents many stability and control challenges that hinder the reliability and resilience of AC grids, particularly during faults. To address this issue, current grid codes require offshore wind farms (OWFs) to remain connected during and after faults. This requirement is challenging because, depending on the fault location and power flow direction, DC link over- or under-voltage can occur, potentially leading to the shutdown of converter stations. Therefore, this necessitates the proper understanding of key technical concepts associated with the integration of OWFs. To help fill the gap, this article performs an in-depth investigation of existing alternating current fault ride through (ACFRT) techniques of modular multilevel converter-based high-voltage direct current (MMC-HVDC) for OWFs. These techniques include the use of AC/DC choppers, flywheel energy storage devices (FESDs), power reduction strategies for OWFs, and energy optimization of the MMC. This article covers both scenarios of onshore and offshore AC faults. Given the importance of wind turbines (WTs) in transforming wind energy into mechanical energy, this article also presents an overview of four WT topologies. In addition, this article explores the advanced converter topologies employed in HVDC systems to transform three-phase AC voltages to DC voltages and vice versa at each terminal of the DC link. Finally, this article explores the key stability and control concepts, such as small signal stability and large disturbance stability, followed by future research trends in the development of converter topologies for HVDC transmission such as hybrid HVDC systems, which combine current source converters (CSCs) and voltage source converters (VSCs) and diode rectifier-based HVDC (DR-HVDC) systems. Full article
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<p>Status of Global OWF Market [<a href="#B7-energies-17-05308" class="html-bibr">7</a>,<a href="#B8-energies-17-05308" class="html-bibr">8</a>].</p>
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<p>Schematic diagram of MMC [<a href="#B4-energies-17-05308" class="html-bibr">4</a>].</p>
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<p>Wind turbine technologies: (<b>a</b>) Type I Fixed Speed Wind Turbine, (<b>b</b>) Type II Variable Speed Wind Turbine, (<b>c</b>) Type III Wind Turbine, (<b>d</b>) Type IV Wind Turbine [<a href="#B32-energies-17-05308" class="html-bibr">32</a>].</p>
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<p>MMC-HVDC system with a DC chopper [<a href="#B52-energies-17-05308" class="html-bibr">52</a>].</p>
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<p>(<b>a</b>) DC link voltages at MMC converter stations 1 and 2. (<b>b</b>) Active power at MMC converter stations 1 and 2 [<a href="#B4-energies-17-05308" class="html-bibr">4</a>].</p>
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<p>Power dissipation at chopper [<a href="#B4-energies-17-05308" class="html-bibr">4</a>].</p>
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<p>MMC-HVDC system with communication links [<a href="#B63-energies-17-05308" class="html-bibr">63</a>].</p>
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<p>Power injected to PMSM and flywheel speed during L-L fault [<a href="#B66-energies-17-05308" class="html-bibr">66</a>].</p>
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<p>(<b>a</b>) Three-phase to ground fault with AEC off. (<b>b</b>) Three-phase to ground fault with AEC on [<a href="#B74-energies-17-05308" class="html-bibr">74</a>].</p>
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<p>DC bus voltage vs. power characteristic of the DC voltage controller [<a href="#B96-energies-17-05308" class="html-bibr">96</a>].</p>
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<p>LOS mechanism during a severe symmetrical grid fault. (<b>a</b>) Unstable PLL frequency, (<b>b</b>) DQ-axis currents relative to the PLL phase angle, (<b>c</b>) DQ-axis currents relative to the actual phase angle of the PCC voltage, and (<b>d</b>) three-phase voltage at the PCC [<a href="#B122-energies-17-05308" class="html-bibr">122</a>].</p>
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27 pages, 5894 KiB  
Article
A Comprehensive Assessment of Storage Elements in Hybrid Energy Systems to Optimize Energy Reserves
by Muhammad Sarmad Raza, Muhammad Irfan Abid, Muhammad Akmal, Hafiz Mudassir Munir, Zunaib Maqsood Haider, Muhammad Omer Khan, Basem Alamri and Mohammed Alqarni
Sustainability 2024, 16(20), 8730; https://doi.org/10.3390/su16208730 - 10 Oct 2024
Viewed by 1855
Abstract
As the world’s demand for sustainable and reliable energy source intensifies, the need for efficient energy storage systems has become increasingly critical to ensuring a reliable energy supply, especially given the intermittent nature of renewable sources. There exist several energy storage methods, and [...] Read more.
As the world’s demand for sustainable and reliable energy source intensifies, the need for efficient energy storage systems has become increasingly critical to ensuring a reliable energy supply, especially given the intermittent nature of renewable sources. There exist several energy storage methods, and this paper reviews and addresses their growing requirements. In this paper, the energy storage options are subdivided according to their primary discipline, including electrical, mechanical, thermal, and chemical. Different possible options for energy storage under each discipline have been assessed and analyzed, and based on these options, a handsome discussion has been made analyzing these technologies in the hybrid mode for efficient and reliable operation, their advantages, and their limitations. Moreover, combinations of each storage element, hybrid energy storage systems (HESSs), are systems that combine the characteristics of different storage elements for fulfilling the gap between energy supply and demand. HESSs for different storage systems such as pumped hydro storage (PHS), battery bank (BB), compressed air energy storage (CAES), flywheel energy storage system (FESS), supercapacitor, superconducting magnetic coil, and hydrogen storage are reviewed to view the possibilities for hybrid storage that may help to make more stable energy systems in the future. This review of combinations of different storage elements is made based on the previous literature. Moreover, it is assessed that sodium-sulfur batteries, lithium-ion batteries, and advanced batteries are the most helpful element in HESSs, as they can be hybridized with different storage elements to fulfill electricity needs. The results also show that HESSs outperformed other storage systems and, hence, hybridizing the characteristics of different storage elements can be employed for optimizing the performance of energy storage systems. Full article
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<p>Energy storage systems hierarchy.</p>
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<p>Classification of supercapacitors as (<b>a</b>) electrochemical double-layer supercapacitors, (<b>b</b>) hybrid supercapacitors, and (<b>c</b>) pseudo supercapacitors, based on electrode materials. Reprinted/adapted with permission from Afif A. et al.; published by Elsevier, 2019 [<a href="#B26-sustainability-16-08730" class="html-bibr">26</a>].</p>
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<p>Hybrid battery supercapacitor storage system.</p>
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<p>The design and relationship of superconducting magnetic energy storage (SMES) components.</p>
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<p>Schematic diagram of pumped hydro storage system.</p>
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<p>(<b>a</b>) Diabatic compressed air energy storage is shown, including the charge and discharge process and the fuel combustion used to heat the compressed air; the process is 50% efficient with regards to its cycle energy. Reprinted/adapted with permission from Tong Z. et al.; published by Elsevier, 2021 [<a href="#B71-sustainability-16-08730" class="html-bibr">71</a>]. (<b>b</b>) Adiabatic compressed air energy storage is shown, including the charge and discharge process. The adiabatic compressed air energy storage is more efficient than diabatic compressed air energy storage, with leading efficiency of more than 60–70%.</p>
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<p>Shapes of flywheel including thick-ring, solid-disk, disk of Laval, and thin-ring flywheel.</p>
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<p>CSP expected capacities forecast (GW) by 2030 showing the trend of countries towards CSP.</p>
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<p>CSP statistics for 2040 showing the fast-growing trend of countries towards CSP.</p>
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<p>CSP statistics showing the trend of countries towards CSP.</p>
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<p>Parabolic trough system with a model showing its components.</p>
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<p>Solar power tower system with heliostats focusing the solar intensity at the tower.</p>
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<p>10 MW PS-10 solar power tower in Seville, Spain.</p>
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<p>Construction of two 50 kW dish stirling systems near Riyadh in Saudi Arabia.</p>
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<p>The system for storage of energy includes a power condition system (PCS), battery management system (BMS), energy management system (EMS), and battery packs.</p>
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<p>Comparison of hydrogen storage materials’ capacity and release temperature relative to system targets for efficient hydrogen storage.</p>
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<p>MESS systems including different technologies based on using new trends.</p>
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14 pages, 8270 KiB  
Article
Design and Analysis of a Highly Reliable Permanent Magnet Synchronous Machine for Flywheel Energy Storage
by Xinjian Jiang, Lei Zhang, Fuwang Li and Zhenghui Zhao
Machines 2024, 12(9), 655; https://doi.org/10.3390/machines12090655 - 19 Sep 2024
Viewed by 775
Abstract
This article aims to propose a highly reliable permanent magnet synchronous machine (PMSM) for flywheel energy-storage systems. Flywheel energy-storage systems are large-capacity energy storage technologies suitable for the short-term storage of electrical energy. PMSMs have been used in the flywheel energy-storage systems due [...] Read more.
This article aims to propose a highly reliable permanent magnet synchronous machine (PMSM) for flywheel energy-storage systems. Flywheel energy-storage systems are large-capacity energy storage technologies suitable for the short-term storage of electrical energy. PMSMs have been used in the flywheel energy-storage systems due to their advantages. One of the key requirements for PMSMs in flywheel energy-storage systems is high reliability. A double redundant winding structure is adopted to ensure fault-tolerant operation of the PMSM. The stator is designed with auxiliary teeth to reduce the short-circuit current. Moreover, the number of slots and poles is determined to ensure the winding factor, heat dissipation, and reduce losses. Moreover, the dual three-phase stator winding structure and auxiliary teeth are adopted on the PMSM to improve reliability. Afterward, the electromagnetic performance is analyzed, and the mechanical stress is investigated to ensure mechanical strength. Finally, a prototype is built and tested to verify the theoretical analysis and performance of the PMSM. Full article
(This article belongs to the Section Electrical Machines and Drives)
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<p>Topology of proposed PMSM. (<b>a</b>) Stator. (<b>b</b>) Rotor.</p>
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<p>Winding connection.</p>
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<p>Different winding structures and slot vector star diagrams. (<b>a</b>) Conventional double-layer, three-phase winding. (<b>b</b>) Dual three-phase winding.</p>
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<p>Stator magnetomotive force distributions generated by each set of windings.</p>
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<p>Stator magnetomotive force distributions under the different winding structures. (<b>a</b>) Conventional double-layer three-phase winding. (<b>b</b>) Dual three-phase winding.</p>
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<p>Harmonic order of stator magnetomotive force distributions.</p>
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<p>Size of the auxiliary teeth.</p>
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<p>Variation of self-inductance and mutual inductance with length of auxiliary teeth.</p>
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<p>Variation of self-inductance and mutual inductance with width of auxiliary teeth.</p>
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<p>Variation of short-circuit current and torque with width of auxiliary teeth.</p>
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<p>Comparison of short-circuit current of PMSM. (<b>a</b>) Peak short-circuit current. (<b>b</b>) Steady state short-circuit current.</p>
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<p>Back electromotive force of PMSM. (<b>a</b>) Back electromotive force waveform. (<b>b</b>) Harmonic orders.</p>
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<p>Self-inductance and mutual inductance of PMSM.</p>
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<p>Torque performance of PMSM. (<b>a</b>) Cogging torque. (<b>b</b>) Torque.</p>
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<p>Mechanical stress and deformation of rotor core. (<b>a</b>) Mechanical stress. (<b>b</b>) Deformation.</p>
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<p>Prototype. (<b>a</b>) Stator. (<b>b</b>) Rotor.</p>
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<p>Experimental platform.</p>
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<p>Comparison of experimental and simulated results. (<b>a</b>) Back electromotive force of prototype. (<b>b</b>) Comparison of back electromotive force coefficient.</p>
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<p>Low-load experimental waveform.</p>
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16 pages, 12121 KiB  
Article
Hardware-in-the-Loop Simulation of Flywheel Energy Storage Systems for Power Control in Wind Farms
by Li Yang and Qiaoni Zhao
Electronics 2024, 13(18), 3610; https://doi.org/10.3390/electronics13183610 - 11 Sep 2024
Viewed by 585
Abstract
Flywheel energy storage systems (FESSs) are widely used for power regulation in wind farms as they can balance the wind farms’ output power and improve the wind power grid connection rate. Due to the complex environment of wind farms, it is costly and [...] Read more.
Flywheel energy storage systems (FESSs) are widely used for power regulation in wind farms as they can balance the wind farms’ output power and improve the wind power grid connection rate. Due to the complex environment of wind farms, it is costly and time-consuming to repeatedly debug the system on-site. To save research costs and shorten research cycles, a hardware-in-the-loop (HIL) testing system was built to provide a convenient testing environment for the research of FESSs on wind farms. The focus of this study is the construction of mathematical models in the HIL testing system. Firstly, a mathematical model of the FESS main circuit is established using a hierarchical method. Secondly, the principle of the permanent magnet synchronous motor (PMSM) is analyzed, and a nonlinear dq mathematical model of the PMSM is established by referring to the relationship among d-axis inductance, q-axis inductance, and permanent magnet flux change with respect to the motor’s current. Then, the power grid and wind farm test models are established. Finally, the established mathematical models are applied to the HIL testing system. The experimental results indicated that the HIL testing system can provide a convenient testing environment for the optimization of FESS control algorithms. Full article
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<p>Structural diagram of wind farms with FESSs.</p>
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<p>The structure of HIL testing systems.</p>
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<p>Circuit of the network-side inverter.</p>
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<p>Circuit of A-phase bridge arm.</p>
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<p>Circuit of a single IGBT: (<b>a</b>) original circuit; (<b>b</b>) equivalent circuit.</p>
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<p>Equivalent circuit of A-phase bridge arm.</p>
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<p>Equivalent circuit of the inductive filter.</p>
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<p>Equivalent circuit of the capacitive filter.</p>
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<p>Equivalent circuit of the support capacitor.</p>
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<p>PMSM model.</p>
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<p>Topological structure of the power grid test model.</p>
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<p>Topological structure of wind farm test models.</p>
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<p>Motor-side waveform.</p>
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<p>Power adjustment strategy from experience.</p>
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<p>FESS output power when there is positive disturbance: (<b>a</b>) under the charging state; (<b>b</b>) under the discharge state.</p>
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<p>FESS output power when there is negative disturbance: (<b>a</b>) under the charging state and (<b>b</b>) under the discharge state.</p>
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<p>Comparison of wind farm output power.</p>
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28 pages, 12309 KiB  
Article
Optimising Flywheel Energy Storage Systems: The Critical Role of Taylor–Couette Flow in Reducing Windage Losses and Enhancing Heat Transfer
by Mahmoud Eltaweel and Mohammad Reza Herfatmanesh
Energies 2024, 17(17), 4466; https://doi.org/10.3390/en17174466 - 5 Sep 2024
Cited by 1 | Viewed by 959
Abstract
Amidst the growing demand for efficient and sustainable energy storage solutions, Flywheel Energy Storage Systems (FESSs) have garnered attention for their potential to meet modern energy needs. This study uses Computational Fluid Dynamics (CFD) simulations to investigate and optimise the aerodynamic performance of [...] Read more.
Amidst the growing demand for efficient and sustainable energy storage solutions, Flywheel Energy Storage Systems (FESSs) have garnered attention for their potential to meet modern energy needs. This study uses Computational Fluid Dynamics (CFD) simulations to investigate and optimise the aerodynamic performance of FESSs. Key parameters such as radius ratio, aspect ratio, and rotational velocity were analysed to understand their impact on windage losses and heat transfer. This study reveals the critical role of Taylor–Couette flow on the aerodynamic performance of FESSs. The formation of Taylor vortices within the airgap was examined, demonstrating their effect on temperature distribution and overall system performance. Through a detailed examination of the skin friction coefficient and Nusselt number under different conditions, this study identified a nonlinear relationship between rotor temperature and rotational speed, highlighting the accelerated temperature rise at higher speeds. The findings indicate that optimising these parameters can significantly enhance the efficiency of FESSs, reducing windage losses and improving heat transfer. This research provides valuable insights into the aerodynamic and thermal optimisation of FESSs, offering pathways to improve their design and performance. The results contribute to advancing guidelines for the effective implementation of FESSs in the energy sector, promoting more sustainable energy storage solutions. Full article
(This article belongs to the Special Issue The Past, Present, and Future of Flywheel Energy Storage)
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<p>Numerical domain: (<b>a</b>) FESS geometry in 3D, (<b>b</b>) the simplified geometry with periodic and symmetry regions.</p>
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<p>Nusselt number vs. skin friction coefficient for the five tested meshes at different RR values: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>R</mi> <mo>=</mo> <mn>0.99</mn> </mrow> </semantics></math>, (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>R</mi> <mo>=</mo> <mn>0.98</mn> </mrow> </semantics></math>, (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>R</mi> <mo>=</mo> <mn>0.97</mn> </mrow> </semantics></math>, (<b>d</b>) <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>R</mi> <mo>=</mo> <mn>0.96</mn> </mrow> </semantics></math>, and (<b>e</b>) <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>R</mi> <mo>=</mo> <mn>0.95</mn> </mrow> </semantics></math>.</p>
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<p>Comparison of average velocity profile between current CFD with Hosain et al. [<a href="#B26-energies-17-04466" class="html-bibr">26</a>] and H. Reichardt [<a href="#B27-energies-17-04466" class="html-bibr">27</a>].</p>
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<p>Air velocity distribution within the airgap of a FESS with a RR of 0.99 at different rotational speeds: (<b>a</b>) 200 rad/s, (<b>b</b>) 800 rad/s, (<b>c</b>) 1600 rad/s, and (<b>d</b>) 2400 rad/s.</p>
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<p>Velocity vector plot within the airgap of a FESS with a RR of 0.99 at different rotational speeds: (<b>a</b>) 200 rad/s, (<b>b</b>) 800 rad/s, (<b>c</b>) 1600 rad/s, and (<b>d</b>) 2400 rad/s. The dotted lines indicate the boundaries of a Taylor vortex, each of which consists of two vortex cells.</p>
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<p>Linear velocity as a function of distance at the midpoint of the FESS airgap with a RR of 0.99.</p>
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<p>The comparison of CFD and computed Taylor cell numbers as a function of Taylor number at a RR of 0.975.</p>
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<p>Velocity vector plot within the airgap of a FESS operating at 1600 rad/s at different RRs: (<b>a</b>) 0.99, (<b>b</b>) 0.98, (<b>c</b>) 0.97, and (<b>d</b>) 0.96. The dotted lines indicate the boundaries of a Taylor vortex, each of which consists of two vortex cells.</p>
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<p>Air velocity distribution within the airgap of a FESS operating at 1600 rad/s at different RRs: (<b>a</b>) 0.99, (<b>b</b>) 0.98, (<b>c</b>) 0.97, and (<b>d</b>) 0.96.</p>
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<p>Temperature distribution within the airgap of a FESS operating at 1600 rad/s at different RRs: (<b>a</b>) 0.99, (<b>b</b>) 0.98, (<b>c</b>) 0.97, and (<b>d</b>) 0.96.</p>
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<p>Enlarged velocity vectors within the airgap of a FESS operating at 1600 rad/s with a RR of 0.96.</p>
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<p>Contour plot illustrating the examined section of axial velocity in the Z-Y plane within the airgap of a FESS operating at 1600 rad/s with a RR of 0.96.</p>
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<p>Contour plot of axial velocity in the Z-Y plane within the gap of a FESS operating at 1600 rad/s at different RRs: (<b>a</b>) 0.96, (<b>b</b>) 0.97, (<b>c</b>) 0.98, and (<b>d</b>) 0.99.</p>
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<p>Contour plot of radial velocity in the Z-Y plane within the airgap of a FESS operating at 1600 rad/s at different RRs: (<b>a</b>) 0.96, (<b>b</b>) 0.97, (<b>c</b>) 0.98, and (<b>d</b>) 0.99.</p>
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<p>Contour plot of tangential velocity in the Z-Y plane within the airgap of a FESS operating at 1600 rad/s at different RRs: (<b>a</b>) 0.96, (<b>b</b>) 0.97, (<b>c</b>) 0.98, and (<b>d</b>) 0.99.</p>
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<p>Linear velocity as a function of distance at the midpoint of the FESS airgap with a RR of 0.98 operating at different operational speeds.</p>
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<p>Linear velocity as a function of distance at the midpoint of the FESS airgap with a RR of 0.97 operating at different operational speeds.</p>
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<p>Linear velocity as a function of distance at the midpoint of the FESS airgap with a RR of 0.96 operating at different operational speeds.</p>
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<p>Skin friction coefficient vs. Taylor number for different RRs.</p>
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<p>Taylor number vs. rotational speed for different RRs.</p>
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<p>Skin friction coefficient vs. rotational speed for different RRs.</p>
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<p>Rotor temperature vs. rotational speed for different RRs.</p>
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<p>Windage losses vs. rotational speed for different RRs.</p>
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<p>Reynolds number vs. rotational speed for different RRs.</p>
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<p>Taylor number vs. Reynolds number for different RRs.</p>
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<p>Windage losses vs. Taylor number for different RRs.</p>
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<p>Nusselt number vs. rotational speed for different RRs.</p>
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<p>Nusselt number vs. Taylor number for different RRs.</p>
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16 pages, 2422 KiB  
Article
Hybrid-Energy Storage Optimization Based on Successive Variational Mode Decomposition and Wind Power Frequency Modulation Power Fluctuation
by Changqing Chen, Weihua Tang, Yunqing Xia and Chang Chen
Energies 2024, 17(17), 4391; https://doi.org/10.3390/en17174391 - 2 Sep 2024
Cited by 1 | Viewed by 803
Abstract
In order to solve the problem of frequency modulation power deviation caused by the randomness and fluctuation of wind power outputs, a method of auxiliary wind power frequency modulation capacity allocation based on the data decomposition of a “flywheel + lithium battery” hybrid-energy [...] Read more.
In order to solve the problem of frequency modulation power deviation caused by the randomness and fluctuation of wind power outputs, a method of auxiliary wind power frequency modulation capacity allocation based on the data decomposition of a “flywheel + lithium battery” hybrid-energy storage system was proposed. Firstly, the frequency modulation power deviation caused by the uncertainty of wind power is decomposed by the successive variational mode decomposition (SVMD) method, and the mode function is segmented and reconstructed by high and low frequencies. Secondly, a mathematical model is established to maximize the economic benefit of energy storage considering the frequency modulation mileage, and quantum particle swarm optimization is used to solve the target model considering the charging and discharging power of energy storage and the charging state constraints to obtain the optimal hybrid-energy storage configuration. Finally, the simulation results show that, in the step disturbance, the Δfmax of the hybrid-energy storage mode is reduced by 37.9% and 15.3%, respectively, compared with single-energy storage. Under continuous disturbance conditions, compared with the single-energy storage mode, the Δfp_v is reduced by 52.73%, 43.72%, 60.71%, and 47.62%, respectively. The frequency fluctuation range is obviously reduced, and the frequency stability is greatly improved. Full article
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<p>Topology of mixed-air storage system.</p>
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<p>Hybrid-energy storage frequency modulation power distribution strategy.</p>
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<p>Optimization process of hybrid-energy storage capacity.</p>
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<p>Frequency deviation power.</p>
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<p>IMF components decomposed by different methods.</p>
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<p>Frequency deviation under different modes.</p>
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<p>Frequency deviation under different modes.</p>
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42 pages, 5426 KiB  
Review
Integration and Optimization of Multisource Electric Vehicles: A Critical Review of Hybrid Energy Systems, Topologies, and Control Algorithms
by Nikolaos Fesakis, Georgios Falekas, Ilias Palaiologou, Georgia Eirini Lazaridou and Athanasios Karlis
Energies 2024, 17(17), 4364; https://doi.org/10.3390/en17174364 - 31 Aug 2024
Viewed by 2539
Abstract
Electric vehicles (EVs) are pivotal in addressing the escalating environmental crisis. While EV drivetrains excel compared to those of vehicles with internal combustion engines (ICEs), their energy storage systems are hampered by limited range, lifespan, and lengthy charging times. Hybrid energy storage systems [...] Read more.
Electric vehicles (EVs) are pivotal in addressing the escalating environmental crisis. While EV drivetrains excel compared to those of vehicles with internal combustion engines (ICEs), their energy storage systems are hampered by limited range, lifespan, and lengthy charging times. Hybrid energy storage systems (HESSs) present a viable current solution to these issues. This review thoroughly explores the state of the art in the emerging field of multisource EVs that utilize HESSs, incorporating any combination of batteries (BTs), supercapacitors (SCs), flywheels (FWs), fuel cells (FCs), and/or transmotors. In addition, the paper systematically categorizes and evaluates different hybrid configurations, detailing potential topologies and their respective advantages and limitations. Moreover, the paper examines diverse control algorithms used to manage these complex systems, focusing on their effectiveness and operational efficiency. By identifying current research gaps and technological challenges, this study aims to delineate future research directions that could enhance the deployment and optimization of multisource EVs, thereby addressing critical challenges such as energy density, system reliability, and cost-effectiveness. Full article
(This article belongs to the Section E: Electric Vehicles)
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<p>(<b>a</b>) Composition of BT cell from current: Lithium iron phosphate battery (LFP)-type cell [<a href="#B18-energies-17-04364" class="html-bibr">18</a>]. (<b>b</b>) Functional diagram of FC of proton exchange membrane (PEM) type [<a href="#B19-energies-17-04364" class="html-bibr">19</a>].</p>
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<p>Schematic representation of electrical double-layer capacitor (EDLC) [<a href="#B33-energies-17-04364" class="html-bibr">33</a>].</p>
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<p>(<b>a</b>) Structure and components of FW [<a href="#B39-energies-17-04364" class="html-bibr">39</a>]. (<b>b</b>) Transmotor–FW powertrain system.</p>
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<p>(<b>a</b>) Passive cascade battery and supercapacitor configuration. (<b>b</b>) Active cascade system (active cascade supercapacitor and battery configuration).</p>
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<p>(<b>a</b>) Active cascade system with reverse battery and supercapacitor connectivity (active cascade battery and supercapacitor configuration). (<b>b</b>) Parallel passive cascade system with two DC/DC converters.</p>
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<p>(<b>a</b>) Multiple converter configuration. (<b>b</b>) Multi-input converter configuration.</p>
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<p>(<b>a</b>) Direct parallel connection/semi-active topology. (<b>b</b>) Indirect parallel connection/active topology.</p>
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<p>(<b>a</b>) Direct parallel connection of fuel cell and battery. (<b>b</b>) Direct parallel connection of fuel cell.</p>
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<p>(<b>a</b>) Direct parallel connection of battery. (<b>b</b>) Indirect parallel connection of fuel cell and battery.</p>
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<p>(<b>a</b>) Battery and fuel cell parallel direct connection. (<b>b)</b> Supercapacitor parallel direct connection.</p>
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<p>(<b>a</b>) Battery parallel direct connection. (<b>b</b>) Parallel indirect connection of battery, supercapacitor, and fuel cell.</p>
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<p>Independent control of multiple fuel cell stacks in hybrid powertrain topology.</p>
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<p>Integrated hybrid power system with fuel cell and FESS in urban transit application.</p>
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<p>EMS algorithms for multisource EVs categorization.</p>
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32 pages, 3035 KiB  
Review
Review of Hybrid Energy Storage Systems for Hybrid Electric Vehicles
by Ahtisham Urooj and Ali Nasir
World Electr. Veh. J. 2024, 15(8), 342; https://doi.org/10.3390/wevj15080342 - 30 Jul 2024
Cited by 2 | Viewed by 3667
Abstract
Energy storage systems play a crucial role in the overall performance of hybrid electric vehicles. Therefore, the state of the art in energy storage systems for hybrid electric vehicles is discussed in this paper along with appropriate background information for facilitating future research [...] Read more.
Energy storage systems play a crucial role in the overall performance of hybrid electric vehicles. Therefore, the state of the art in energy storage systems for hybrid electric vehicles is discussed in this paper along with appropriate background information for facilitating future research in this domain. Specifically, we compare key parameters such as cost, power density, energy density, cycle life, and response time for various energy storage systems. For energy storage systems employing ultra capacitors, we present characteristics such as cell voltage, cycle life, power density, and energy density. Furthermore, we discuss and evaluate the interconnection topologies for existing energy storage systems. We also discuss the hybrid battery–flywheel energy storage system as well as the mathematical modeling of the battery–ultracapacitor energy storage system. Toward the end, we discuss energy efficient powertrain for hybrid electric vehicles. Full article
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<p>Hybrid energy storage system (HESS) power train of ICE based HEVs.</p>
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<p>Types of hybrid electric vehicles.</p>
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<p>Series HEV.</p>
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<p>Parallel HEV.</p>
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<p>Series-parallel HEV.</p>
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<p>Complex HEV.</p>
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<p>Active cascade UC/battery configuration.</p>
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<p>Passive cascade battery/UC configuration.</p>
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<p>Active cascade battery/UC configuration.</p>
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<p>Passive cascade with 2 DC-DC converter configurations.</p>
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<p>Multiple DC-DC converter configuration.</p>
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<p>Multiple DC-DC converter configuration.</p>
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<p>Four recent DC-DC converter configurations.</p>
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<p>Novel DC-DC converter configuration.</p>
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<p>EV with flywheel energy storage systems.</p>
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<p>Energy management strategies for HEV.</p>
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18 pages, 8462 KiB  
Article
Fatigue Life of Flywheel Energy Storage Rotors Composed of 30Cr2Ni4MoV Steel
by Dongxu Hu, Xingjian Dai, Bo Xie, Wen Li, Hongyan Yu and Haisheng Chen
Energies 2024, 17(15), 3730; https://doi.org/10.3390/en17153730 - 29 Jul 2024
Cited by 1 | Viewed by 897
Abstract
In supporting the stable operation of high-penetration renewable energy grids, flywheel energy storage systems undergo frequent charge–discharge cycles, resulting in significant stress fluctuations in the rotor core. This paper investigates the fatigue life of flywheel energy storage rotors fabricated from 30Cr2Ni4MoV alloy steel, [...] Read more.
In supporting the stable operation of high-penetration renewable energy grids, flywheel energy storage systems undergo frequent charge–discharge cycles, resulting in significant stress fluctuations in the rotor core. This paper investigates the fatigue life of flywheel energy storage rotors fabricated from 30Cr2Ni4MoV alloy steel, attempting to elucidate the material’s mechanical properties, crack propagation behavior, and impact of internal defects on fatigue life. Tensile tests reveal that the material exhibited high yield (992 MPa) and tensile strengths (1130 MPa). The Paris formula is used to model crack growth rates, ending in good agreement with the experimental data. Fatigue tests at various stress conditions highlight the material’s significant variability in fatigue life and emphasize the need for reliable design approaches. This paper also demonstrates that internal defect size and location critically affect fatigue life, calling for improvements in forging inspection standards. Overall, the present study provides a comprehensive analysis of 30Cr2Ni4MoV steel’s suitability for flywheel rotors, balancing safety, and operational efficiency. Full article
(This article belongs to the Special Issue The Past, Present, and Future of Flywheel Energy Storage)
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<p>Frequency fluctuations—high frequency 24 h dataset components [<a href="#B6-energies-17-03730" class="html-bibr">6</a>].</p>
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<p>Internal structure diagram of the flywheel. 1. Lower support component; 2. rotor component; 3. motor component; 4. upper support component.</p>
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<p>Material strength testing equipment.</p>
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<p>Tensile stress–strain curve of 30Cr2Ni4MoV steel.</p>
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<p>Crack propagation test specimen of 30Cr2Ni4MoV steel.</p>
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<p>Crack propagation curve.</p>
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<p>Comparison of crack propagation rates [<a href="#B15-energies-17-03730" class="html-bibr">15</a>].</p>
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<p>Relationship between fracture toughness and yield strength of 30Cr2Ni4MoV steel.</p>
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<p>Fatigue testing equipment.</p>
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<p>Technical drawing of the fatigue-testing specimen [<a href="#B19-energies-17-03730" class="html-bibr">19</a>].</p>
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<p>Fatigue testing status.</p>
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<p>Fatigue life <span class="html-italic">N</span>/cycles.</p>
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<p>Mean fatigue life <span class="html-italic">N</span>/cycles.</p>
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<p>Comparison of model predictions with experimental results.</p>
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<p>The effect of maximum stress on fatigue life when the stress amplitude is constant.</p>
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<p>The effect of stress ratio on fatigue life when the maximum stress is constant.</p>
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<p>Stress state of a rotating disk [<a href="#B20-energies-17-03730" class="html-bibr">20</a>].</p>
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<p>Stress contour map of the flywheel rotor.</p>
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<p>Stress contour map.</p>
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<p>Stress distribution path.</p>
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<p>Stress variation curve.</p>
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<p>Stress contour map with an internal defect.</p>
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<p>Stress contour map of defect location.</p>
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<p>Effect of defect location on fatigue life.</p>
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<p>Effect of defect size on fatigue life.</p>
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<p>The relationship between total stored energy and rotational speed.</p>
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<p>Flywheel energy storage unit placed underground.</p>
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26 pages, 8942 KiB  
Article
Energy Management of Green Port Multi-Energy Microgrid Based on Fuzzy Logic Control
by Yu Deng and Jingang Han
Energies 2024, 17(14), 3601; https://doi.org/10.3390/en17143601 - 22 Jul 2024
Cited by 1 | Viewed by 1033
Abstract
The green port multi-energy microgrid, featuring renewable energy generation, hydrogen energy, and energy storage systems, is an important gateway to achieve the net-zero emission goal. But there are many forms of energy in green port multi-energy microgrid systems, the power fluctuates frequently, and [...] Read more.
The green port multi-energy microgrid, featuring renewable energy generation, hydrogen energy, and energy storage systems, is an important gateway to achieve the net-zero emission goal. But there are many forms of energy in green port multi-energy microgrid systems, the power fluctuates frequently, and the port loads with large fluctuations and fast changes. These factors can easily lead to the problem of the state of charge exceeding the limit of the energy storage system. To distribute the fluctuating power in the green port multi-energy microgrid system reasonably and maintain the state of charge (SOC) of the hybrid energy storage system in an moderate range, an energy management strategy (EMS) based on dual-stage fuzzy control with a low pass-filter algorithm is proposed in this paper. First, the mathematical model of a green port multi-energy microgrid system is established. Then, fuzzy rules are designed, and the dual-stage fuzzy controller is used to change the time constant of the low-pass filter (LPF) and modify the initial power distribution by an LPF algorithm. Finally, simulation models are built in Matlab 2016a/Simulink. The simulation results demonstrate that, compared with other algorithms under the control of the EMS proposed in this paper, the high-frequency component in the flywheel power is smaller, and the SOC of the supercapacitor is maintained in a reasonable range of 34–78%, which extends the lifespan of the flywheel and supercapacitor. Additionally, it has a faster automatic adjustment ability for the state of charge of the energy storage system, which is conducive to better maintaining the stable operation of green port multi-energy microgrid systems. Full article
(This article belongs to the Section A1: Smart Grids and Microgrids)
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<p>Green port multi-energy microgrid system and EMS.</p>
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<p>Equivalent electrical circuit of PV cells.</p>
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<p>Power–wind speed diagram of generator.</p>
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<p>Solar irradiance and wind speed within a day.</p>
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<p>Schematic diagram of a craning cycle.</p>
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<p>Power curve of craning cycle of quay crane.</p>
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<p>Number of berthing ships at port.</p>
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<p>Load power of port.</p>
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<p>Structure diagram of DSFCLPF-EMS.</p>
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<p>(<b>a</b>) Input membership function of FSFC; (<b>b</b>) Output membership function of FSFC.</p>
Full article ">Figure 11
<p>(<b>a</b>) Input membership function <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>sc</mi> </mrow> </msub> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>; (<b>b</b>) input membership function <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="italic">SOC</mi> </mrow> <mrow> <mi>sc</mi> </mrow> </msub> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>; (<b>c</b>) input membership function <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>; (<b>d</b>) output membership function <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>sc</mi> </mrow> </msub> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>.</p>
Full article ">Figure 11 Cont.
<p>(<b>a</b>) Input membership function <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>sc</mi> </mrow> </msub> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>; (<b>b</b>) input membership function <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="italic">SOC</mi> </mrow> <mrow> <mi>sc</mi> </mrow> </msub> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>; (<b>c</b>) input membership function <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>; (<b>d</b>) output membership function <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>sc</mi> </mrow> </msub> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>.</p>
Full article ">Figure 12
<p>Simulation model of the green port multi-energy microgrid system.</p>
Full article ">Figure 13
<p>Load power and grid power of port.</p>
Full article ">Figure 14
<p>Power of hybrid energy storage system.</p>
Full article ">Figure 15
<p>The time constant and the power of the supercapacitor and flywheel.</p>
Full article ">Figure 16
<p>(<b>a</b>) Change rate of flywheel power of DSFCLPF algorithm; (<b>b</b>) Change rate of flywheel power of WPD; (<b>c</b>) Change rate of flywheel power of SFC.</p>
Full article ">Figure 17
<p>(<b>a</b>) SOC of supercapacitor of DSFCLPF algorithm; (<b>b</b>) SOC of supercapacitor of WPD; (<b>c</b>) SOC of supercapacitor of SFC.</p>
Full article ">Figure 18
<p>SOC change in supercapacitor for extreme value of initial SOC. (<b>a</b>) Initial SOC is 10%; (<b>b</b>) initial SOC is 90%.</p>
Full article ">Figure 19
<p>SOC of supercapacitor within one month.</p>
Full article ">Figure 20
<p>Change rate of flywheel power within one month.</p>
Full article ">Figure A1
<p>(<b>a</b>) Input membership function <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>fly</mi> </mrow> </msub> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>; (<b>b</b>) input membership function <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="italic">SOC</mi> </mrow> <mrow> <mi>fly</mi> </mrow> </msub> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>; (<b>c</b>) input membership function <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>; (<b>d</b>) output membership function <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>fly</mi> </mrow> </msub> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>.</p>
Full article ">Figure A1 Cont.
<p>(<b>a</b>) Input membership function <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>fly</mi> </mrow> </msub> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>; (<b>b</b>) input membership function <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="italic">SOC</mi> </mrow> <mrow> <mi>fly</mi> </mrow> </msub> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>; (<b>c</b>) input membership function <math display="inline"><semantics> <mrow> <mi>T</mi> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>; (<b>d</b>) output membership function <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>fly</mi> </mrow> </msub> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>.</p>
Full article ">
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