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Keywords = Hybrid Bus

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17 pages, 926 KiB  
Article
State of Change-Related Hybrid Energy Storage System Integration in Fuzzy Sliding Mode Load Frequency Control Power System with Electric Vehicles
by Yuzhe Xie, Peng Liao, Zhihao Liang and Dan Zhou
Machines 2025, 13(1), 57; https://doi.org/10.3390/machines13010057 - 16 Jan 2025
Viewed by 270
Abstract
In the context of the integration of hybrid energy storage systems (HESSs) and electric vehicles (EVs), this paper investigates the load frequency control (LFC) issue of the power system. Weighting coefficients are set for the generators, HESSs and EVs, respectively, to show their [...] Read more.
In the context of the integration of hybrid energy storage systems (HESSs) and electric vehicles (EVs), this paper investigates the load frequency control (LFC) issue of the power system. Weighting coefficients are set for the generators, HESSs and EVs, respectively, to show their different abilities to regulate the power system. A fuzzy logic-based sliding mode control approach is designed to ensure the stable performance of the LFC power system integrated with HESSs and EVs. The improvement of the proposed method is the application of the linear matrix inequality (LMI) toolbox in fuzzy controller design, which solves the limitations and uncertainties caused by trial-error or experience in common fuzzy controllers. There is no general form for the membership function of the fuzzy control. This paper presents a design approach for the membership function based on the calculation results of LMI. Simulations are tested on an IEEE 39-bus system integrated with HESSs and EVs. The simulation results prove that the proposed method reduces the time required for the power system frequency to reach stability by approximately 8.8%, demonstrating the superiority and usability of the proposed approach. Full article
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19 pages, 9423 KiB  
Article
A Common DC Bus Circulating Current Suppression Method for Motor Emulators of New Energy Vehicles
by Haonan Sun, Dafang Wang, Qi Li and Yingkang Qin
Machines 2025, 13(1), 51; https://doi.org/10.3390/machines13010051 - 13 Jan 2025
Viewed by 327
Abstract
In contrast to the conventional topology, wherein the Device Under Test (DUT) controller and the electric motor emulator (EME) are powered by the DC (Direct Current) voltage source independently, the common DC bus topology necessitates a single power supply. This reduces the cost [...] Read more.
In contrast to the conventional topology, wherein the Device Under Test (DUT) controller and the electric motor emulator (EME) are powered by the DC (Direct Current) voltage source independently, the common DC bus topology necessitates a single power supply. This reduces the cost and complexity of the motor emulator system, making it more favorable for large-scale industrial applications. However, this topology introduces significant circulating current issues in the system. A common DC bus circulating current suppression method is proposed in this paper for the motor emulator. First, the mechanism of zero-sequence circulating current generation in the common DC bus topology is analyzed and the expression for the system’s zero-sequence voltage difference is derived. Then, a control method based on a Hybrid PWM (Pulse Width Modulation) strategy that unifies SPWM (SIN Pulse Width Modulation) and SVPWM (Space Vector Pulse Width Modulation) is proposed, which has been shown to be effective in suppressing the zero-sequence circulating current in a motor emulator system with a common DC bus topology. The proposed control method has been experimentally validated using a motor emulator system. Full article
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36 pages, 15998 KiB  
Article
A Modular and Scalable Approach to Hybrid Battery and Converter Integration for Full-Electric Waterborne Transport
by Ramon Lopez-Erauskin, Argiñe Alacano, Aitor Lizeaga, Giuseppe Guidi, Olve Mo, Amaia Lopez-de-Heredia and Mikel Alzuri
J. Mar. Sci. Eng. 2025, 13(1), 120; https://doi.org/10.3390/jmse13010120 - 11 Jan 2025
Viewed by 417
Abstract
This paper presents a flexible and scalable battery system for maritime transportation, integrating modular converters and hybrid battery technologies that are effectively implemented in real-world scenarios. The proposed system is realized with modular DC-DC converters, which do not require complex design and control [...] Read more.
This paper presents a flexible and scalable battery system for maritime transportation, integrating modular converters and hybrid battery technologies that are effectively implemented in real-world scenarios. The proposed system is realized with modular DC-DC converters, which do not require complex design and control or a high number of components and combine high-power (HP) and high-energy (HE) battery cells to optimize the energy and power requirements of vessel operations without oversizing the energy storage system. Moreover, the modular design ensures flexibility and scalability, allowing for easy adaptation to varying operational demands. In particular, the system topology, control mechanisms, and communication protocols are explained in this paper. The concept has been validated through simulations and real-scale laboratory tests, demonstrating its effectiveness. Key results highlight the system’s ability to maintain the DC bus voltage while operating at high efficiency (ranging from 97% to 98%) under different load conditions, supported by reliable and demanding real-time communication using the EtherCAT standard. This real-time capability has been validated, and related results are presented in this paper, showing a synchronization accuracy below 200 ns between two modules and a stable control at a cycle time of 400 µs. This approach offers a promising solution for reducing greenhouse gas emissions in the maritime industry, aligning with global sustainability goals. Full article
(This article belongs to the Special Issue Advanced Technologies for New (Clean) Energy Ships)
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18 pages, 3255 KiB  
Article
Explainable Warm-Start Point Learning for AC Optimal Power Flow Using a Novel Hybrid Stacked Ensemble Method
by Kaijie Xu, Xiaochen Zhang and Lin Qiu
Sustainability 2025, 17(2), 438; https://doi.org/10.3390/su17020438 - 8 Jan 2025
Viewed by 446
Abstract
With the development of renewable energy, renewable power generation has become an increasingly important component of the power system. However, it also introduces uncertainty into the analysis of the power system. Therefore, to accelerate the solution of the OPF problem, this paper proposes [...] Read more.
With the development of renewable energy, renewable power generation has become an increasingly important component of the power system. However, it also introduces uncertainty into the analysis of the power system. Therefore, to accelerate the solution of the OPF problem, this paper proposes a novel Hybrid Stacked Ensemble Method (HSEM), which incorporates explainable warm-start point learning for AC optimal power flow. The HSEM integrates conventional machine learning techniques, including regression trees and random forests, with gradient boosting trees. This combination leverages the individual strengths of each algorithm, thereby enhancing the overall generalization capabilities of the model in addressing AC-OPF problems and improving its interpretability. Experimental results indicate that the HSEM model achieves superior accuracy in AC-OPF solutions compared to traditional Deep Neural Network (DNN) approaches. Furthermore, the HSEM demonstrates significant improvements in both the feasibility and constraint satisfaction of control variables. The effectiveness of the proposed HSEM is validated through rigorous testing on the IEEE-30 bus system and the IEEE-118 bus system, demonstrating its ability to provide an explainable warm-start point for solving AC-OPF problems. Full article
(This article belongs to the Section Energy Sustainability)
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29 pages, 5928 KiB  
Article
Energy Management Strategy for Direct Current Microgrids with Consideration of Photovoltaic Power Tracking Optimization
by Fudong Li, Zonghao Shi, Zhihao Zhu and Yongjun Gan
Energies 2025, 18(2), 252; https://doi.org/10.3390/en18020252 - 8 Jan 2025
Viewed by 371
Abstract
In response to the uncertainty of renewable energy output and the fluctuation of load, this paper proposes a hybrid energy storage management strategy based on the State of Charge (SOC) to smooth power fluctuations and thereby improve the power quality of photovoltaic energy [...] Read more.
In response to the uncertainty of renewable energy output and the fluctuation of load, this paper proposes a hybrid energy storage management strategy based on the State of Charge (SOC) to smooth power fluctuations and thereby improve the power quality of photovoltaic energy storage DC microgrids. Firstly, a hybrid algorithm for power tracking control is formed by incorporating the Particle Swarm Optimization (PSO) algorithm into the variable step-size Incremental Conductance (INC) method, thereby optimizing the maximum power point tracking control system of the photovoltaic system. Then, a first-order filter is employed for the initial allocation of demand power. Taking the SOC of supercapacitors and energy storage batteries as a reference, a secondary power allocation energy management strategy based on rule-based control is proposed to ensure the service life and application safety of the hybrid energy storage system. Finally, simulation experiments are conducted in MATLAB/Simulink 23.2 (R2023b). The results indicate that the proposed energy management strategy can maintain the SOC of the hybrid energy storage system at a reasonable level and effectively smooth DC bus voltage fluctuations. Full article
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25 pages, 5036 KiB  
Article
Research on Low-Latency TTP–TSN Cross-Domain Network Planning Problem
by Yifei Peng, Tigang Jiang, Xiaodong Tu, Bolin Huang, Zheng Guo and Du Xu
Electronics 2025, 14(1), 203; https://doi.org/10.3390/electronics14010203 - 6 Jan 2025
Viewed by 476
Abstract
With services becoming increasingly complex and network scales expanding, hybrid network architectures that combine bus and switch networks while supporting deterministic transmission will play a crucial role in future networks. Time-Triggered Protocol (TTP) and Time-Sensitive Networking (TSN), as key protocols currently ensuring time [...] Read more.
With services becoming increasingly complex and network scales expanding, hybrid network architectures that combine bus and switch networks while supporting deterministic transmission will play a crucial role in future networks. Time-Triggered Protocol (TTP) and Time-Sensitive Networking (TSN), as key protocols currently ensuring time determinism in bus and switch networks, respectively, are of significant importance for research on hybrid network architectures and ensuring deterministic communication across protocols. In this paper, firstly, we analyzed the causes of latency in TTP–TSN hybrid networks. To reduce latency, we designed a cross-protocol time-synchronization algorithm. And, based on network-wide time synchronization, we constructed a joint TTP–TSN low-latency scheduling model, using Integer Linear Programming (ILP), which was then solved by an ILP solver. Based on this scheduling model, we proposed a heuristic fast scheduling algorithm and proofs of its schedulability and approximation ratio. Finally, we designed simulation and prototype systems for verification. Our experimental results demonstrate that the time-synchronization algorithm proposed in this paper achieves a synchronization error of no more than 1 µs. Compared to the case without applying the joint scheduling model, the fast heuristic algorithm can reduce end-to-end latency by at least 50%, and shorten the solving time by thousands of times compared to an ILP solver, all while ensuring schedulability. Full article
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25 pages, 9795 KiB  
Article
Research on the Integrated Converter and Its Control for Fuel Cell Hybrid Electric Vehicles with Three Power Sources
by Yuang Ma and Wenguang Luo
Electronics 2025, 14(1), 29; https://doi.org/10.3390/electronics14010029 - 25 Dec 2024
Viewed by 410
Abstract
Separate DC-DC converters for each energy source are typically configured in fuel-cell hybrid vehicles. This results in a complex control structure of the powertrain system, low energy density of the converter, and high cost due to the large number of components. Conducting research [...] Read more.
Separate DC-DC converters for each energy source are typically configured in fuel-cell hybrid vehicles. This results in a complex control structure of the powertrain system, low energy density of the converter, and high cost due to the large number of components. Conducting research on DC-DC converters with good energy flow management and high integration is a trend to solve such problems. Based on the analysis of the basic functional structure of the converter, this paper designs a buffering unit circuit with energy collection and distribution functions and appropriately connects it with the pulse unit circuit of the converter. Through device optimization reuse and power transmission path integration, a class of non-isolated four-port DC-DC converters is constructed, which consists of an auxiliary energy charging module, input energy source control module, braking energy feedback module and forward bootstrap boost circuit. This converter has two bi-directional ports, a uni-directional input and a bi-directional output, for separate connection to the power batteries, supercapacitors, fuel cells and DC bus. It can adapt to the fluctuation of the vehicle’s driving condition while achieving dynamic and flexible regulation of power flow and can flexibly allocate power according to the load current and voltage level of energy. It can realize a total of 14 operation modes, including six output power supply operation modes, five auxiliary power charging operation modes, and three braking energy regeneration operation modes. Furthermore, the mathematical model of this converter is constructed using the state-average method and the small-signal modeling method in order to achieve the responsiveness and stability of switching multiple operating modalities. The PI control parameters are optimized using the particle swarm optimization algorithm to achieve optimized control of the converter. The simulation system is set up using MATLAB R2024a to verify that the proposed converter topology and algorithm can dynamically allocate appropriate current paths to manipulate the power flow under various operating conditions, effectively improving the utilization rate and efficiency of energy. The converter has the characteristics of high gain and high power density, which is suitable for three-energy fuel cell hybrid electric vehicles. Full article
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20 pages, 8938 KiB  
Article
Equivalent Cost Minimization Strategy for Plug-In Hybrid Electric Bus with Consideration of an Inhomogeneous Energy Price and Battery Lifespan
by Di Xue, Haisheng Wang, Junnian Wang, Changyang Guan and Yiru Xia
Sustainability 2025, 17(1), 46; https://doi.org/10.3390/su17010046 - 25 Dec 2024
Viewed by 355
Abstract
The development of energy-saving vehicles is an important measure to deal with environmental pollution and the energy crisis. On this basis, more accurate and efficient energy management strategies can further tap into the energy-saving potential and energy sustainability of vehicles. The equivalent consumption [...] Read more.
The development of energy-saving vehicles is an important measure to deal with environmental pollution and the energy crisis. On this basis, more accurate and efficient energy management strategies can further tap into the energy-saving potential and energy sustainability of vehicles. The equivalent consumption minimization strategy (ECMS) has shown the ability to provide a real-time sub-optimal fuel efficiency performance. However, when taking the different market prices of fuel and electricity cost as well as battery longevity cost into account, this method is not very accurate for total operational economic evaluation. So, as an improved scheme, the instantaneous cost minimization strategy is proposed, where a comprehensive cost function, including the market price of the electricity and fuel as well as the cost of battery aging, is applied as the optimization objective. Simulation results show that the proposed control strategy for series-parallel hybrid electric buses can reduce costs by 41.25% when compared with the conventional engine-driven bus. The approach also impressively improves cost performance over the rule-based strategy and the ECMS. As such, the proposed instantaneous cost minimization strategy is a better choice for hybrid electric vehicle economic evaluation than the other main sub-optimal strategies. Full article
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29 pages, 4639 KiB  
Article
Design and Experimental Validation of a Battery/Supercapacitor Hybrid Energy Storage System Based on an Adaptive LQG Controller
by Jhoan Alejandro Montenegro-Oviedo, Carlos Andres Ramos-Paja, Martha Lucia Orozco-Gutierrez, Edinson Franco-Mejía and Sergio Ignacio Serna-Garcés
Appl. Syst. Innov. 2025, 8(1), 1; https://doi.org/10.3390/asi8010001 - 25 Dec 2024
Viewed by 458
Abstract
Hybrid energy storage systems (HESSs) are essential for adopting sustainable energy sources. HESSs combine complementary storage technologies, such as batteries and supercapacitors, to optimize efficiency, grid stability, and demand management. This work proposes a semi-active HESS formed by a battery connected to the [...] Read more.
Hybrid energy storage systems (HESSs) are essential for adopting sustainable energy sources. HESSs combine complementary storage technologies, such as batteries and supercapacitors, to optimize efficiency, grid stability, and demand management. This work proposes a semi-active HESS formed by a battery connected to the DC bus and a supercapacitor managed by a Sepic/Zeta converter, which has the aim of avoiding high-frequency variations in the battery current on any operation condition. The converter control structure is formed by an LQG controller, an optimal state observer, and an adaptive strategy to ensure the correct controller operation in any condition: step-up, step-down, and unitary gain. This adaptive LQG controller consists of two control loops, an internal current loop and an external voltage loop, which use only two sensors. Compared with classical PI and LQG controllers, the adaptive LQG solution exhibits a better performance in all operation modes, up to 68% better than the LQG controller and up to 84% better than the PI controller. Therefore, the control strategy proposed for this HESS provides a fast-tracking of DC-bus current, driving the high-frequency component to the supercapacitor and the low-frequency component to the battery. Thus, fast changes in the battery power are avoided, reducing the degradation. Finally, the system adaptability to changes up to 67% in the operation range are experimentally tested, and the implementation of the control system using commercial hardware is verified. Full article
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35 pages, 13847 KiB  
Article
Sigma Delta Modulation Controller and Associated Cybersecurity Issues with Battery Energy Storage Integrated with PV-Based Microgrid
by Syeda Afra Saiara and Mohd. Hasan Ali
Energies 2024, 17(24), 6463; https://doi.org/10.3390/en17246463 - 22 Dec 2024
Viewed by 556
Abstract
Battery energy storage systems (BESSs) play a crucial role in integrating renewable energy sources into microgrids. However, robust BESS controllers are needed to carry out this function properly. Existing controllers suffer from overshoots and slow convergence issues. Moreover, as electrical grid networks become [...] Read more.
Battery energy storage systems (BESSs) play a crucial role in integrating renewable energy sources into microgrids. However, robust BESS controllers are needed to carry out this function properly. Existing controllers suffer from overshoots and slow convergence issues. Moreover, as electrical grid networks become increasingly connected, the risk of cyberattacks grows, and traditional physics-based anomaly detection methods face challenges such as reliance on predefined models, high computational demands, and limited scalability for complex, large-scale data. To address the limitations of the existing approaches, this paper first proposes a novel sigma-delta modulation (SDM) controller for BESSs in solar photovoltaic (PV)-connected microgrids. The performance of SDM has been compared with those of the proportional–integral (PI) controller and fuzzy logic controller (FLC). Also, this paper proposes an improved ensemble-based method to detect the false data injection (FDI) and denial-of-service (DoS) attacks on the BESS controller. The performance of the proposed detection method has been compared with that of the traditional ensemble-based method. Four PV-connected microgrid systems, namely the solar DC microgrid, grid-connected solar AC microgrid, hybrid AC microgrid with two BESSs, and hybrid AC microgrid with a single BESS, have been considered to show the effectiveness of the proposed control and detection methods. The MATLAB/Simulink-based results show the effectiveness and better performance of the proposed controller and detection methods. Numerical results demonstrate the improved performance of the proposed SDM controller, with a 35% reduction in AC bus voltage error compared to the conventional PI controller and FLC. Similarly, the proposed SAMME AdaBoost detection method achieves superior accuracy with an F1 score of 95%, outperforming the existing ensemble approaches. Full article
(This article belongs to the Section A1: Smart Grids and Microgrids)
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15 pages, 7418 KiB  
Article
Research on Speed Planning and Energy Management Strategy for Fuel Cell Hybrid Bus in Green Wave Scenarios at Traffic Light Intersections Based on Deep Reinforcement Learning
by Fengyan Yi, Wei Guo, Hongtao Gong, Yang Shen, Jiaming Zhou, Wenhao Yu, Dagang Lu, Chunchun Jia, Caizhi Zhang and Farui Gong
Sustainability 2024, 16(24), 11156; https://doi.org/10.3390/su162411156 - 19 Dec 2024
Viewed by 612
Abstract
In the context of intelligent and connected transportation, obtaining the real-time vehicle status and comprehensive traffic data is crucial for addressing challenges related to speed optimization and energy regulation in intricate transportation situations. This paper introduces a control method for the speed optimization [...] Read more.
In the context of intelligent and connected transportation, obtaining the real-time vehicle status and comprehensive traffic data is crucial for addressing challenges related to speed optimization and energy regulation in intricate transportation situations. This paper introduces a control method for the speed optimization and energy management of a fuel cell hybrid bus (FCHB) based on the Deep Deterministic Policy Gradient (DDPG) algorithm. The strategy framework is built on a dual-objective optimization deep reinforcement learning (D-DRL) architecture, which integrates traffic signal information into the energy management framework, in addition to conventional state spaces to guide control decisions. The aim is to achieve “green wave” traffic while minimizing hydrogen consumption. To validate the effectiveness of the proposed strategy, simulation tests were conducted using the SUMO platform. The results show that in terms of speed planning, the difference between the maximum and minimum speeds of the FCHB was reduced by 21.66% compared with the traditional Intelligent Driver Model (IDM), while the acceleration and its variation were reduced by 8.89% and 13.21%, respectively. In terms of the hydrogen fuel efficiency, the proposed strategy achieved 95.71% of the performance level of the dynamic programming (DP) algorithm. The solution proposed in this paper is of great significance for improving passenger comfort and FCHB economy. Full article
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22 pages, 2870 KiB  
Article
Coordinated Optimization Method for Distributed Energy Storage and Dynamic Reconfiguration to Enhance the Economy and Reliability of Distribution Network
by Caihong Zhao, Qing Duan, Junda Lu, Haoqing Wang, Guanglin Sha, Jiaoxin Jia and Qi Zhou
Energies 2024, 17(23), 6040; https://doi.org/10.3390/en17236040 - 1 Dec 2024
Cited by 1 | Viewed by 562
Abstract
To fully leverage the application potential of distributed energy storage systems (DESS) and network reconfiguration, a coordinated optimization method is proposed to enhance the economic efficiency of distribution networks under normal conditions and the reliability of a power supply during fault conditions. First, [...] Read more.
To fully leverage the application potential of distributed energy storage systems (DESS) and network reconfiguration, a coordinated optimization method is proposed to enhance the economic efficiency of distribution networks under normal conditions and the reliability of a power supply during fault conditions. First, a scenario-generation method is developed based on Latin hypercube sampling and Kantorovich distance synchronous back-substitution reduction is used to obtain the typical scenario of wind and solar output. Next, a planning operation coordinated optimization framework and model are established, considering both normal and fault states of the distribution network. In the planning layer, the objective is to minimize the annual comprehensive capital expenditures for the distribution network to improve the economic efficiency of the distribution network. The operation layer includes both normal operation and fault operation states, with the optimization goal of minimizing the sum of normal operation costs and the fault costs associated with load shedding. Subsequently, a hybrid optimization algorithm combining an improved Aquila Optimizer-Second-Order Cone Programming (IAO-SOCP) is proposed to solve the coordinated optimization model. Finally, the proposed coordinated optimization method is validated using an enhanced IEEE 33-bus distribution network case study. The results demonstrate that the method effectively reduces network losses and minimizes load shedding costs during fault conditions, thereby ensuring a balance between the economic efficiency and reliability of the distribution network. Full article
(This article belongs to the Section A1: Smart Grids and Microgrids)
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27 pages, 3930 KiB  
Article
Importance Evaluation of Power Grid Transmission Lines Based on Multidimensional Information Feature Mapping
by Keji Chen, Yingqi Tie and Maohua Li
Energies 2024, 17(23), 6013; https://doi.org/10.3390/en17236013 - 29 Nov 2024
Viewed by 421
Abstract
The importance evaluation of power grid transmission lines is crucial for preventing catastrophic grid failures, enhancing grid resilience, and ensuring the safe and stable operation of the power system. To address the limitations in existing transmission line evaluation methods, such as reliance on [...] Read more.
The importance evaluation of power grid transmission lines is crucial for preventing catastrophic grid failures, enhancing grid resilience, and ensuring the safe and stable operation of the power system. To address the limitations in existing transmission line evaluation methods, such as reliance on single evaluation metrics, insufficient consideration of information transmission between adjacent lines, and the impact of line failures on system load loss, this paper proposes a comprehensive evaluation method based on multidimensional information feature mapping. First, evaluation metrics are established from three dimensions—power transmission characteristics, grid network structure, and resilience improvement—each reflecting the importance of transmission lines from different perspectives. Then, a hybrid weighting method is introduced, combining subjective and objective weights through a game theory approach to calculate the comprehensive weights, enabling the multidimensional information-based importance evaluation of transmission lines. Finally, an improved network efficiency index, representing the current operational performance of the grid, is developed to validate the proposed evaluation method. A simulation analysis using the IEEE-39 bus test system verifies the feasibility and accuracy of the proposed approach. Full article
(This article belongs to the Section F4: Critical Energy Infrastructure)
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25 pages, 5497 KiB  
Article
Transient Stability-Based Fast Power System Contingency Screening and Ranking
by Teshome Lindi Kumissa and Fekadu Shewarega
Electricity 2024, 5(4), 947-971; https://doi.org/10.3390/electricity5040048 - 25 Nov 2024
Viewed by 725
Abstract
Today’s power systems are operated closer to their stability limits due to the continuously growing load demands, interface to open markets, and integration of more renewable energies. In order to provide operators with clear insight on the current system situation, near real-time power [...] Read more.
Today’s power systems are operated closer to their stability limits due to the continuously growing load demands, interface to open markets, and integration of more renewable energies. In order to provide operators with clear insight on the current system situation, near real-time power systems dynamic security assessment tools are required. One of the core elements of near real-time dynamic security assessment tools is contingency screening and ranking. Most of the commercially available tools screen and rank contingencies by using the traditional numerical integration or Transient Energy Functions (TEFs) or hybrid methods. The traditional numerical integration method is accurate but computationally intensive and has a slow assessment speed which makes it difficult to identify any insecure contingency before it happens. Despite the TEF method of transient stability analysis being relatively fast, it develops less accurate results due to models simplification and assumptions. This paper introduces transient stability based on fast and robust contingency screening and ranking using an Adaptive step-size Differential Transformation (AsDTM) method. Based on the most current snapshot from Supervisory Control and Data Accusation (SCADA) data, the proposed method triggers AsDTM-based transient stability simulation for each credible contingency and evaluates Transient Stability Indices (TSI) as the normalized weighted sum of squares of errors derived from state variables and complex bus voltages at every simulation time step. Finally, contingencies are ranked based on these TSI and the worst contingency is identified for the next detail assessment. The method is tested on IEEE 9 bus and 39 bus test systems. Test results reveal that the proposed method is faster, robust, and can be used in near real-time dynamic security assessment sessions. Full article
(This article belongs to the Special Issue Advances in Operation, Optimization, and Control of Smart Grids)
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36 pages, 8468 KiB  
Article
A Novel Magnetic Integration High-Efficiency Converter with Low Ripple and High Dynamic Response for the Hybrid Power Supply Systems of All-Electric Aircraft
by Li Chen, Haifeng Gao, Fengjie Shen, Yiyi Zhang, Liangjie Qiu and Lei Wang
Aerospace 2024, 11(12), 965; https://doi.org/10.3390/aerospace11120965 - 25 Nov 2024
Viewed by 720
Abstract
With the continuous improvement of battery energy density and converter power density, as well as the miniaturization and lightweighting of related airborne electrical equipment, all-electric aircraft with hybrid power supply systems provide more trade-off space and possibilities for the design of future aircraft. [...] Read more.
With the continuous improvement of battery energy density and converter power density, as well as the miniaturization and lightweighting of related airborne electrical equipment, all-electric aircraft with hybrid power supply systems provide more trade-off space and possibilities for the design of future aircraft. It is indispensable to search for a more valuable topology and apply it to airborne power supply. This paper proposes an airborne high-gain unidirectional DC-DC converter suitable for between low-voltage unit and high-voltage bus, which consists of interleaved magnetic integrated switched coupled inductor units and improved switch capacitor units. This paper first analyzes the steady-state operating characteristics under different modes; the new topology has higher voltage gain and lower stress. Secondly, in response to the challenges of high efficiency and high power density, we propose a magnetic integration design method and comprehensive experimental scheme based on the EIE-type magnetic core structure. This successfully integrates multiple discrete inductors into a single magnetic core. Furthermore, based on the comprehensive consideration of steady-state, transient performance and power density, the general design criteria for a high-gain switched coupled inductor are summarized through the equivalent mathematical model of reverse flux coupling. Additionally, by adjusting the coupling coefficient, the converter can achieve zero-voltage switching under light load conditions, demonstrating versatility and scalability and better meeting the application requirements of electric aircraft. The proposed prototype can provide voltage gain in the range of 12–22 times the input voltage gain by varying the input voltage from a 12–24 V fuel cell. The comprehensive performance of the converter, including steady-state, transient, and efficiency, was tested under D < 0.5 and D > 0.5. The experimental results show that the proposed converter possesses advantages such as high gain and low stress, a high dynamic response and low ripple, and high efficiency and high power density, which can provide a more advantageous DC-DC converter solution for airborne hybrid power supply systems. Full article
(This article belongs to the Special Issue Electric Power Systems and Components for All-Electric Aircraft)
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