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State-of-the-Art of Power Systems
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State-of-the-Art of Power Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: 20 October 2024 | Viewed by 16232

Special Issue Editors

Dr. Chunyu Chen

E-Mail Website
Guest Editor
School of Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China
Interests: power system operation and contol
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Dongsheng Yu

E-Mail Website
Guest Editor
School of Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China
Interests: power converters; renewable generation; nonlinear circuits and their application; high-power EV chargers
Special Issues, Collections and Topics in MDPI journals
Dr. Muhammad Junaid

E-Mail Website
Guest Editor
School of Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China
Interests: high voltage power equipment; machine learning techniques in high voltage engineering; arc modeling; cryogenic dielectrics; superconducting power devices for power grid; SF6 gas alternatives
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Kaifeng Zhang

E-Mail Website
Guest Editor
School of Automation, Southeast University, Nanjing 210096, China
Interests: power system control; power system optimization; power market
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Power system technology has been transforming rapidly. New and improved topologies with advanced systems and power grids have recently been undergoing rapid development. With the emergence of 5G technology, its realization and implementation in smart grid systems is receiving significant consideration. The latest trends in the power systems are geared towards clean-and-green energy, more resilient power systems, and modernized smart grids.

The aim of this Special Issue (SI) entitled “State-of-the-Art Power Systems” is to capture the innovative concepts by means of design, analysis, experiments, and case studies that will bolster the move towards an improved power system.

This Special Issue is proposed for publication in Applied Sciences, an MDPI journal. It is an international, peer-reviewed, open-access journal on all aspects of applied natural sciences published semimonthly online. Applied Sciences is indexed by several renowned databases, such as WoS (SCIE Impact Factor 2.679, Q2) and SCOPUS (Elsevier). This SI seeks to publish innovative research works on modern and state-of-the-art power systems. Topics for this Special Issue include, but are not limited to:

  • HVDC power transmission and distribution;
  • Renewable energy based microgrid;
  • New technologies in smart grids;
  • Dynamics and stability of power systems;
  • Power converters penetrated in power systems;
  • Operation and control of power systems;
  • Latest trends in power equipment technology;
  • SF6-free alternatives for state-of-the-art power systems;
  • Cyber-security of distributed power grids;
  • Applications of machine learning in power systems;
  • Power system communications;
  • Power system resilience;
  • New methods in arc quenching;
  • Applications of superconductivity in power systems.

Dr. Chunyu Chen
Prof. Dr. Dongsheng Yu
Dr. Muhammad Junaid
Prof. Dr. Kaifeng Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • power systems
  • smart grids
  • microgrids
  • distributed power systems
  • high voltage
  • power systems control

Published Papers (14 papers)

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Research

18 pages, 3716 KiB  
Article
Partial Discharge Signal Denoising Algorithm Based on Aquila Optimizer–Variational Mode Decomposition and K-Singular Value Decomposition
by Jun Zhong, Zhenyu Liu and Xiaowen Bi
Appl. Sci. 2024, 14(7), 2755; https://doi.org/10.3390/app14072755 - 25 Mar 2024
Viewed by 356
Abstract
Partial discharge (PD) is a primary factor leading to the deterioration of insulation in electrical equipment. However, it is hard for traditional methods to precisely extract PD signals in increasingly complex engineering environments. This paper proposes a new PD signal denoising method combining [...] Read more.
Partial discharge (PD) is a primary factor leading to the deterioration of insulation in electrical equipment. However, it is hard for traditional methods to precisely extract PD signals in increasingly complex engineering environments. This paper proposes a new PD signal denoising method combining Aquila Optimizer–Variational Mode Decomposition (AO-VMD) and K-Singular Value Decomposition (K-SVD) algorithms. Firstly, the AO algorithm optimizes critical parameters of the VMD algorithm. For the PD signal overwhelmed by noise, the AO-VMD algorithm can decompose it and reconstruct it by using kurtosis. In this process, the majority of the noise is removed, and the characteristics of the original signal are shown. Subsequently, the K-SVD algorithm performs sparse decomposition on the signal after OA-VMD, constructs a learned dictionary, and captures the characteristics of the signal for continuous learning and updating. After the dictionary learning is completed, the best matching atoms from the dictionary are selected to precisely reconstruct the original noiseless signal. Finally, the proposed method is compared with three traditional algorithms, Adaptive Ensemble Empirical Mode Decomposition (AEEMD), SVD-VMD, and the Adaptive Wavelet Multilevel Soft Threshold algorithm, on the simulated signal and the actual engineering signal. The results both demonstrate that the algorithm proposed by this paper has superior noise reduction and signal extraction performance. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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18 pages, 3078 KiB  
Article
Distributed Generation Cluster Division Method Considering Frequency Regulation Response Speed
by Yan Xu, Peng Hu, Fengyang Zhang and Tao Zhou
Appl. Sci. 2024, 14(6), 2432; https://doi.org/10.3390/app14062432 - 13 Mar 2024
Viewed by 445
Abstract
With the large-scale integration of distributed generation (DG), it is difficult to realize distribution network planning and operation under specific requirements using the traditional cluster division method based on a single criterion. To reduce the complexity of frequency regulation control strategies, this paper [...] Read more.
With the large-scale integration of distributed generation (DG), it is difficult to realize distribution network planning and operation under specific requirements using the traditional cluster division method based on a single criterion. To reduce the complexity of frequency regulation control strategies, this paper proposes a cluster division method that synthesizes structural and functional indexes. First, the ability of DG within a cluster to provide flexibility to the system is analyzed. Then, a cluster response speed model is proposed to cope with the frequency regulation of demand flexibility on shorter time scales. Based on the above analysis, this paper proposes a distributed generation cluster (DGC) frequency regulation response speed index. The combined electrical distance based on the impedance–power reserve (I–PR) is defined by considering the power reserve of each node of the system. The I–PR is weighted to the structural indexes to improve the division. Meanwhile, in order to enhance the convergence speed of the algorithm for the division process, an adaptive genetic algorithm (GA) based on the encoding method of the weighted network adjacency matrix is used. Finally, distributed generation cluster division is performed on two systems to verify the validity of the proposed indexes in this paper. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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14 pages, 6002 KiB  
Article
Effect of Shunt Resistor Value on the Performance of Resistive Superconducting Fault Current Limiters
by Hamoud Alafnan, Diaa-Eldin A. Mansour, Xiaoze Pei, Moanis Khedr, Mansoor Alturki, Abdullah Albaker, Ibrahim Alsaleh and Xianwu Zeng
Appl. Sci. 2023, 13(20), 11339; https://doi.org/10.3390/app132011339 - 16 Oct 2023
Viewed by 808
Abstract
Resistive-type superconducting fault current limiters (r-SFCLs) have generated great interest for research and technical applications. This is attributed to their superior features, which include self-action, fast response, and simple operation. In low line impedance systems, r-SFCLs are seen as a viable protective mechanism [...] Read more.
Resistive-type superconducting fault current limiters (r-SFCLs) have generated great interest for research and technical applications. This is attributed to their superior features, which include self-action, fast response, and simple operation. In low line impedance systems, r-SFCLs are seen as a viable protective mechanism for limiting high-magnitude fault currents. However, overcurrent caused by faults results in an increased temperature of the r-SFCL, possibly damaging the coils. Thus, the r-SFCL must be appropriately engineered to protect it while still allowing for effective fault current limitation. To achieve this goal, an appropriately sized shunt resistor must be used. Adding a shunt resistor benefits the r-SFCL in several ways, from lowering its maximum temperature to speeding up its recovery. Additionally, the shunt resistor protects the r-SFCL from excessive surges in temperature by giving the current an alternative path to flow down, thus saving it from further damage. A multilayer thermoelectric model was developed to examine the thermoelectrical behavior of the r-SFCL coil throughout a fault occurrence and the subsequent recovery period using three shunt resistors ranging from 4 to 16 Ω. MATLAB®/Simulink was used as the simulation platform in this study. The dependence of the current limitation capability and the voltage profile on the shunt resistor value was studied compared to the basic case without an r-SFCL. Increasing the shunt resistor value led to an enhanced ability to limit fault currents, although at the cost of higher temperatures and a longer recovery time. This study also presents guidance for optimizing the design parameters of r-SFCLs. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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26 pages, 4021 KiB  
Article
Research on Low-Frequency Oscillation Damping Control of Wind Storage System Based on Pareto and Improved Particle Swarm Algorithm
by Yu Song and Shouyuan Wu
Appl. Sci. 2023, 13(18), 10054; https://doi.org/10.3390/app131810054 - 6 Sep 2023
Cited by 1 | Viewed by 1071
Abstract
Aiming at the low-frequency oscillation problem of high-proportion wind power and energy storage connected to the power system, this paper establishes a system small signal model according to the matrix similarity theory, which lays a foundation for the research on oscillation characteristics, mechanism [...] Read more.
Aiming at the low-frequency oscillation problem of high-proportion wind power and energy storage connected to the power system, this paper establishes a system small signal model according to the matrix similarity theory, which lays a foundation for the research on oscillation characteristics, mechanism analysis, and suppression measures. Combined with the different installation positions of the inverter-side converter and the inverter-side POD (Power Oscillation Damper) controller of the energy storage device, the suppression mechanism and damping oscillation ability of the two on low-frequency oscillation were analyzed. Under multiple optimization objectives, the parameters of the damping controller are optimized by Pareto and improved particle swarm algorithms. Finally, through Matlab/Simulink simulation, the effectiveness of the Pareto and improved particle swarm algorithm in suppressing low-frequency oscillation of the system is verified. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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18 pages, 4909 KiB  
Article
Short-Term Wind Power Forecasting Based on VMD and a Hybrid SSA-TCN-BiGRU Network
by Yujie Zhang, Lei Zhang, Duo Sun, Kai Jin and Yu Gu
Appl. Sci. 2023, 13(17), 9888; https://doi.org/10.3390/app13179888 - 31 Aug 2023
Cited by 5 | Viewed by 992
Abstract
Wind power generation is a renewable energy source, and its power output is influenced by multiple factors such as wind speed, direction, meteorological conditions, and the characteristics of wind turbines. Therefore, accurately predicting wind power is crucial for the grid operation and maintenance [...] Read more.
Wind power generation is a renewable energy source, and its power output is influenced by multiple factors such as wind speed, direction, meteorological conditions, and the characteristics of wind turbines. Therefore, accurately predicting wind power is crucial for the grid operation and maintenance management of wind power plants. This paper proposes a hybrid model to improve the accuracy of wind power prediction. Accurate wind power forecasting is critical for the safe operation of power systems. To improve the accuracy of wind power prediction, this paper proposes a hybrid model incorporating variational modal decomposition (VMD), a Sparrow Search Algorithm (SSA), and a temporal-convolutional-network-based bi-directional gated recurrent unit (TCN-BiGRU). The model first uses VMD to break down the raw power data into several modal components, and then it builds an SSA-TCN-BIGRU model for each component for prediction, and finally, it accumulates all the predicted components to obtain the wind power prediction results. The proposed short-term wind power prediction model was validated using measured data from a wind farm in China. The proposed VMD-SSA-TCN-BiGRU forecasting framework is compared with benchmark models to verify its practicability and reliability. Compared with the TCN-BiGRU, the symmetric mean absolute percentage error, the mean absolute error, and the root mean square error of the VMD-SSA-TCN-BiGRU model reduced by 34.36%, 49.14%, and 55.94%. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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16 pages, 3961 KiB  
Article
Improved Combined Inertial Control of Wind Turbine Based on CAE and DNN for Temporary Frequency Support
by Ziyang Ji, Jie Zhang, Yi Liu and Tao Zhou
Appl. Sci. 2023, 13(12), 6984; https://doi.org/10.3390/app13126984 - 9 Jun 2023
Viewed by 763
Abstract
With the continuous and large-scale development of renewable energy, there is a prominent decrease in the level of inertia in new power systems. This decrease leads to the weakening of the system’s capability to provide inertia support and frequency regulation during disturbance events. [...] Read more.
With the continuous and large-scale development of renewable energy, there is a prominent decrease in the level of inertia in new power systems. This decrease leads to the weakening of the system’s capability to provide inertia support and frequency regulation during disturbance events. The wind turbines (WT), as the main representatives of renewable energy generation, should be more efficiently involved in the power system frequency regulation dynamics. However, optimal frequency regulation is difficult to achieve through the combined inertial control strategy of wind turbines because it greatly depends on control parameters and fluctuates in different scenarios. To cope with disturbance efficiently and quickly in different scenarios and obtain the optimal frequency regulation results, this paper presents an improved combined inertial intelligent control strategy of WT based on contractive autoencoder (CAE) and deep neural network (DNN). This method obtains the optimal parameters for combined inertial control using the particle swarm optimization (PSO) algorithm, then effectively extracts features from actual data using CAE followed by building a network model to predict the optimal combined inertial control parameters online. To verify and test the proposed method, it is applied in the IEEE 9-bus test system. The simulation results show that the method can obtain optimal control parameters with a faster computational time, good prediction accuracy, and generalization capability. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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21 pages, 3098 KiB  
Article
A Deep Reinforcement Learning Design for Virtual Synchronous Generators Accommodating Modular Multilevel Converters
by Mu Yang, Xiaojie Wu and Maxwell Chiemeka Loveth
Appl. Sci. 2023, 13(10), 5879; https://doi.org/10.3390/app13105879 - 10 May 2023
Viewed by 1280
Abstract
The deep reinforcement learning (DRL) technique has gained attention for its potential in designing “virtual network” controllers. This skill utilizes a novel solution that can avoid the specific parameters and system model required in classical dynamic programming algorithms. However, addressing the issue of [...] Read more.
The deep reinforcement learning (DRL) technique has gained attention for its potential in designing “virtual network” controllers. This skill utilizes a novel solution that can avoid the specific parameters and system model required in classical dynamic programming algorithms. However, addressing the issue of system uncertainties and performance deterioration remains a challenge. To overcome this challenge, the authors propose a new control prototype using a twin delayed deep deterministic policy gradient (TD3)-based adaptive controller, which replaces the conventional virtual synchronous generator (VSG) module in the modular multilevel converter (MMC) control. In this approach, an adaptive programming module is developed using a critic fuzzy network point of view to determine the optimal control policy. The modification presented in this framework is able to improve the system stability and resist disruptions while retaining the merits of the conventional VSG control model. The proposed approach is implemented and tested using the DRL toolbox in MATLAB/Simulink. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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26 pages, 6953 KiB  
Article
Reliability Assessment of Cyber–Physical Distribution Systems Considering Cyber Disturbances
by Buxiang Zhou, Yating Cai, Tianlei Zang, Jiale Wu, Binjie Sun and Shi Chen
Appl. Sci. 2023, 13(6), 3452; https://doi.org/10.3390/app13063452 - 8 Mar 2023
Cited by 3 | Viewed by 1378
Abstract
With the development of communication technology, traditional distribution networks have gradually developed into cyber–physical systems (CPSs), from which the cyber system provides more protection for the grid and brings new security threat–cyber disturbances. Current research cannot scientifically measure the impact of cyber disturbances [...] Read more.
With the development of communication technology, traditional distribution networks have gradually developed into cyber–physical systems (CPSs), from which the cyber system provides more protection for the grid and brings new security threat–cyber disturbances. Current research cannot scientifically measure the impact of cyber disturbances on the system and lacks reliability indices for a comprehensive quantitative assessment of CPS reliability from the perspective of cyber–physical fusion. If the impact of information disturbances on system reliability is not assessed accurately, it will not be possible to provide a scientific and reasonable decision basis for system planning and operation. Therefore, a set of reliability assessment methods and indices for distribution network CPSs considering cyber disturbances is proposed. Firstly, a reliability modeling method combining fault tree and Petri net is proposed to model the reliability of a distribution network CPS, which can improve the efficiency and accuracy of the modeling. Secondly, the system state is divided into two categories: normal operation state and cyberattack state. Then, generalized reliability indices considering cyber disturbances for distribution network CPSs are defined. Finally, through the tests on the modified IEEE RBTS BUS2 distribution network CPS, an analysis of the effects of information component failures, cyberattacks, and access network structures on system reliability is conducted in this paper to verify the efficiency of the proposed method and the rationality of the newly defined reliability indices. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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17 pages, 7827 KiB  
Article
A Virtual Direct Current Control Method of LCL-DAB DC-DC Converters for Fast Transient Response and No Backflow Power
by Mingxue Li, Zimeng Li, Yushun Zhao, Zixiang Wang, Chong Zhang, Shuo Feng and Dongsheng Yu
Appl. Sci. 2023, 13(4), 2075; https://doi.org/10.3390/app13042075 - 5 Feb 2023
Cited by 1 | Viewed by 1433
Abstract
The LCL-type dual active bridge (LCL-DAB) DC-DC converter is a promising part for DC micro-grids due to its high voltage gain and low bridge current, but the issues of backflow power elimination and transient response optimization deserve attention in its operation. In this [...] Read more.
The LCL-type dual active bridge (LCL-DAB) DC-DC converter is a promising part for DC micro-grids due to its high voltage gain and low bridge current, but the issues of backflow power elimination and transient response optimization deserve attention in its operation. In this article, a virtual direct current control (VDCC) method of the LCL-DAB converter for fast transient response and no backflow power is proposed, which can eliminate the backflow power and improve the transient response against the input voltage and load disturbances. With dual-phase-shift (DPS) modulation scheme, the voltage-current characteristics are first analyzed using the phasor method. The small-signal mathematic model of the LCL-DAB converter is then established. The power characteristic is derived so the design regions of no backflow power can be graphed. On this basis, an appropriate outer phase shift ratio can be estimated to ensure a wide range of no backflow power operation. Moreover, a virtual voltage is generated to compensate in the control loop, thus the transient response against disturbances of the LCL-DAB converter can be improved under no backflow power. Simulation and prototype experimental results are presented to verify the feasibility of the proposed VDCC method. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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17 pages, 3861 KiB  
Article
Dispatching Strategy for Low-Carbon Flexible Operation of Park-Level Integrated Energy System
by Qinglin Meng, Guoqiang Zu, Leijiao Ge, Shengwei Li, Liang Xu, Rui Wang, Kecheng He and Shangting Jin
Appl. Sci. 2022, 12(23), 12309; https://doi.org/10.3390/app122312309 - 1 Dec 2022
Cited by 4 | Viewed by 1172
Abstract
In the face of the dual crisis of energy shortages and global warming, the vigorous development of renewable energy represented by wind-solar energy is a significant approach towards achieving energy transition, carbon peaking, and carbon neutrality goals. Targeting the park-level integrated energy system [...] Read more.
In the face of the dual crisis of energy shortages and global warming, the vigorous development of renewable energy represented by wind-solar energy is a significant approach towards achieving energy transition, carbon peaking, and carbon neutrality goals. Targeting the park-level integrated energy system (PIES) with high penetration of wind-solar energy, we propose a day-ahead dispatching strategy that takes into account the flexible supply and the reward-punishment ladder-type carbon trading mechanism (RPLTCTM). Firstly, RPLTCTM and carbon capture equipment (CCE) are considered in the dispatching model, and the mechanism of coordinated operation of CCE and RPLTCTM is explored to further improve the system’s ability to restrain carbon emissions. Secondly, power-based flexibility indicators (PFIs) are adopted to quantitatively evaluate the flexibility supply, and based on the load demand response characteristics, the dispatchable resources on the load side are guided to improve the system’s operation flexibility. On this basis, a multi-objective optimal dispatching model that takes into account the carbon emission cost, energy cost, and flexibility supply are constructed, and the original problem is transformed into a mixed-integer single-objective linear problem through mathematical equivalence and flexibility cost. Finally, simulation examples validate that the economy, flexibility, and low-carbon level of the dispatching plan can be synergistically improved by the proposed strategy. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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11 pages, 3424 KiB  
Article
Study on the Efficiency of Temperature/Strain Measurement for Ultra-Long-Distance Optical Fiber Composite Overhead Power Transmission Lines
by Lidong Lu, Xingchen Su, Chenglong Zhang, Qinghao Gao and Xiande Bu
Appl. Sci. 2022, 12(21), 11043; https://doi.org/10.3390/app122111043 - 31 Oct 2022
Cited by 4 | Viewed by 1255
Abstract
The coherent optical time domain reflectometer (COTDR) is a very important instrument for distributed temperature/strain measurement along the sensing fiber with a large dynamic range and high accuracy. The length of the sensing fiber and the temperature/strain measurement range limit the system performance, [...] Read more.
The coherent optical time domain reflectometer (COTDR) is a very important instrument for distributed temperature/strain measurement along the sensing fiber with a large dynamic range and high accuracy. The length of the sensing fiber and the temperature/strain measurement range limit the system performance, especially the measurement efficiency. So, a COTDR system is constructed, and the characteristics of the obtained coherent Rayleigh noise (CRN) are analyzed. Then, in consideration of the temperature/strain measurement range, accuracy, and time efficiency, the temperature/strain demodulation algorithm in noise conditions is studied. With different noise coefficients, the array length with 11, 21, 31, 51, and 101 independent frequency sweeping points are adopted to calculate the cross-correlation coefficients along a standard reference array with 301 independent frequency sweeping points. The results demonstrate that the array length has little influence on the signal processing time, but it can decide the measurement accuracy. To balance the system measurement efficiency and accuracy, it is inferred that, for a sensing fiber with a length of 100 km or more, the optimal independent frequency sweeping points are 101 and the trace average number is 1000. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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19 pages, 5492 KiB  
Article
Location of Multiple Types of Faults in Active Distribution Networks Considering Synchronization of Power Supply Area Data
by Gang Ren, Xianguang Zha, Bing Jiang, Xiaoli Hu, Junjun Xu and Kai Tao
Appl. Sci. 2022, 12(19), 10024; https://doi.org/10.3390/app121910024 - 6 Oct 2022
Cited by 1 | Viewed by 1114
Abstract
When a short circuit occurs in the power supply area of a distribution network with a high-permeability distributed generation, the line current will increase, the voltage will drop sharply, and the fault characteristics will be more complex. Therefore, the automatic, quick, and accurate [...] Read more.
When a short circuit occurs in the power supply area of a distribution network with a high-permeability distributed generation, the line current will increase, the voltage will drop sharply, and the fault characteristics will be more complex. Therefore, the automatic, quick, and accurate location of fault sections is of great significance to the reliability of power supply. In order to prevent large-scale power outages in the power supply area caused by the failure of feeders and transformers, this paper proposes a novel method to locate fault sections in active distribution networks by taking into account the data of the power supply area. On the basis of the synchronization of calculated and measured time and the observability of the fault state, a limited number of intelligent terminals are reasonably arranged in the distribution network feeder and power supply area. Additionally, the fault location equation is established based on the three-phase voltage change values of the nodes before and after the fault collected by intelligent terminals, so that the fault section is determined by comparing the residuals. Finally, the proposed method is verified by the improved IEEE 37-node and IEEE 123-node three-phase distribution networks. The results show that it has high accuracy in locating fault sections in multiple fault scenarios. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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16 pages, 6139 KiB  
Article
A Double-Side Feedback Pulse Train Control for the Output Voltage Regulation of Two-Stage Wireless Power Transfer System
by Juan Lei, Muhammad Junaid, Dongsheng Yu, Zhuo Hua and Samson Yu
Appl. Sci. 2022, 12(18), 8991; https://doi.org/10.3390/app12188991 - 7 Sep 2022
Cited by 1 | Viewed by 1098
Abstract
Pulse Train (PT) control is a nonlinear voltage regulation method with favorable characteristics of quick response time and simple structure. In this paper, a PT-based feedback control strategy is proposed for stabilizing the output voltage of two-stage wireless power transfer (WPT) systems. Low-frequency [...] Read more.
Pulse Train (PT) control is a nonlinear voltage regulation method with favorable characteristics of quick response time and simple structure. In this paper, a PT-based feedback control strategy is proposed for stabilizing the output voltage of two-stage wireless power transfer (WPT) systems. Low-frequency voltage oscillations can be observed in PT controlled front-stage power converters, which significantly degrades the output power quality of the WPT system. To solve this problem, by using feedback variables sampled from both output sides of a power converter and WPT, a capacitor current and output voltage feedback PT (CC&OV-PT) controlled two-stage WPT system is further devised in this paper. A discrete time model of the two-stage WPT system is established, and the performance of low-frequency voltage oscillations suppression for the double-side feedback CC&OV-PT controlled WPT system is analyzed. Simulation and experimental verification have been conducted, both of which show that the CC&OV-PT controlled WPT system achieves fast response with effective low-frequency oscillation suppression. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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15 pages, 4275 KiB  
Article
Adjustable Capacity Evaluation Method Based on Step-by-Step Power Mapping of Offshore Wind Farms
by Jingtao Zhao, Zhiyong Lv, Xiaofeng Dong, Shu Zheng, Junpeng Zhu and Zhi Wu
Appl. Sci. 2022, 12(17), 8644; https://doi.org/10.3390/app12178644 - 29 Aug 2022
Viewed by 997
Abstract
Offshore wind power has developed rapidly in recent years, but its scale still lags far behind onshore wind power. Offshore wind power still has great development potential. One of the key factors restricting the development of offshore wind power is the unsatisfactory control [...] Read more.
Offshore wind power has developed rapidly in recent years, but its scale still lags far behind onshore wind power. Offshore wind power still has great development potential. One of the key factors restricting the development of offshore wind power is the unsatisfactory control effect of offshore wind farms, and the reason is that the adjustable capacity of the wind farm cannot be obtained accurately and quickly. Aims to meet the high precision requirements for adjustable capacity evaluation of offshore wind farms, this paper establishes a step-by-step power mapping framework based on the division of power transmission processes in offshore wind farms, considering the loss of each transmission process in detail. By establishing a step-by-step mapping from the wind turbine power to the injected power at the grid connection point of the offshore wind farm, the adjustable capacity of the offshore wind farm can be estimated based on the maximum theoretical power of the wind turbines. The performance of proposed method has been demonstrated in a real offshore wind farm. Full article
(This article belongs to the Special Issue State-of-the-Art of Power Systems)
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