bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transformer winding state diagnosis method based on short-circuit impulse response and multi-feature joint
Authors: Chen Yuwen , Sun Qiuya , Huang Yijun , Zhang Feng , Qian Xingxu 
Published: December 2024

Abstract
To investigate the relationship between the physical characteristics of transformer short-circuit impulse signals and winding deformation, this paper proposes a transformer winding state diagnosis method based on the combination of short-circuit impulse response and multiple features. Firstly, based on the relative displacement model of a single degree of freedom system, a winding short-circuit impulse response spectrum is constructed, and the energy entropy characteristics of different frequency bands are extracted using the Hilbert energy spectrum. Secondly, the energy spectrum is converted into a time-frequency matrix, and its energy density distribution and short-term energy attenuation changes are quantified. Then, we perform support vector regression (SVD) decomposition and calculate the proportion of singular value vectors. Finally, multiple feature quantities are combined to construct a feature set, which is then input into the SVD model optimized by the particle swarm algorithm (PSO) for diagnosis. The experimental results show that the proposed method can accurately extract the physical characteristics of short-circuit impulse signals, and the error between the obtained transformer winding deformation diagnosis value and the actual state value is only 3.6%, which can provide guidance for online monitoring of the transformer winding state.
Online monitoring method for inter-turn short circuit fault of dry-type hollow core reactor
Authors: Tang Zhen , Huang Yijun , Sun Qiuya , Yao Hongyang , Qian Xingxu 
Published: December 2024

Abstract
A method for online monitoring of turn-to-turn short circuit faults based on power factor changes is proposed to solve the problem of small overall current changes and delayed overcurrent protection after the occurrence of turn-to-turn short circuit faults in dry-type hollow reactors. A circuit model of inter-turn short-circuit fault reactor was established, and the changes in electrical parameters of the fault reactor were numerically analyzed at different positions. On this basis, the power factor was determined as the monitored variable, and a test platform was built for experimental verification. The research results indicate that after a turn-to-turn short circuit fault, the total current changes very little, the power factor increases significantly, and the changes in various electrical parameters are related to the location of the short circuit. The experimental results are consistent with the theoretical analysis results, verifying the correctness and effectiveness of the monitoring method.
Microwave-based passive wireless electronic transformer development
Authors: Wang Yu , Zhu Jianyang , Qiu Keyue , Dai Qiji , Mao Junyi , He Yumin 
Published: December 2024

Abstract
With the continuous development of intelligent substations and the past demand for intelligent transformation of power grids, electronic transformers have been widely utilized. Given that the active type of electronic transformer was susceptible to electromagnetic interference, particularly on the high-voltage power supply side, disturbances were challenging to evade, leading to its poor reliability. Based on microwave wireless transmission technology, this study theoretically proposed a dynamic wireless energy supply link for electronic transformers and designed a passive wireless electronic transformer utilizing microwave technology. Simultaneously, it developed the corresponding software and hardware systems, constructed an experimental test platform, conducted tests in high-voltage environments, and verified its performance by comparing it with active wired methods. The results demonstrated that the microwave-based passive wireless electronic transformer developed in this paper had good reliability and could be widely applied in practice.
Optimal scheduling of microgrids based on IWSA
Authors: Zhang Shuai , Xianyu Jianchuan 
Published: December 2024

Abstract
Microgrid systems are usually composed of multiple distributed power sources. Smart algorithms are often used to schedule microgrids to reduce operating costs. Smart algorithms are prone to fall into local optimal solutions when solving microgrid scheduling models, resulting in poor solution accuracy. Therefore, based on the white shark algorithm, a mixed-strategy improved white shark algorithm (WSA) is proposed, which improves the white shark optimization algorithm by using three strategies, including Tent chaotic mapping, nonlinearly adjusted convergence factor, and Cauchy variants. The method is designed to ensure that the operation of microgrids achieves the best results in terms of economy by satisfying various system constraints. It is found that the improved algorithm has great improvement in convergence speed, convergence accuracy, and stability, which proves its effectiveness.
Optimal carbon reduction and energy storage management method for new power systems considering carbon emissions
Authors: Liang Shen , Chu Xueli , Wang Peng 
Published: December 2024

Abstract
With the advancement of the national “dual carbon” strategy goals and the planning of new energy systems, the proportion of new energy connected to the power grid is rapidly increasing. Therefore, it is urgent to accelerate the planning and construction of energy storage. In this context, from the perspective of energy storage as a regulatory resource, this paper aims to build a set of energy storage state estimation and residual life prediction methods with high estimation accuracy and low computational complexity and achieve energy storage management on the energy storage management system of edge computing architecture, so as to meet the safe, reliable, lasting and efficient operation needs of the energy storage management system, while promoting wind and solar energy consumption as a means. Taking carbon emission reduction as the optimal goal, energy storage management and utilization methods are built. Through simulation experiments, it is verified that this optimal carbon reduction and energy storage management method has good experimental results.
A new low carbon scheduling method for source load multi time scale in power systems
Authors: Zhao Fei , Yang Li , Chen Jiaxi , Gu Jiting , Pan Li 
Published: December 2024

Abstract
The impact of global climate change caused by carbon dioxide emissions on human production and life is becoming increasingly severe. New energy sources, led by wind and solar power, have become the backbone of reducing carbon emissions. The main focus of this article is to develop advantages such as multi-energy complementarity, efficient integration, flexibility and stability, and low-carbon environmental protection. While meeting the diverse energy needs of the energy consumption side, it is necessary to reasonably allocate resources on the energy supply side and effectively absorb renewable energy. To begin with, this paper develops a multi-time-scale economic dispatch model for a holistic energy system, focusing on collaborative carbon reduction between energy sources and loads. The upper layer serves as a long-term energy scheduling mechanism, dynamically updating electricity prices and conveying them to the lower layer model. The lower layer functions as a short-term energy scheduling component, directing load management according to electricity prices and providing feedback on the load plan to the upper layer model. Both the upper and lower-layer models strive to minimize the overall operational costs as their primary objective. Secondly, the probability distribution of wind and photovoltaic power is discretized using sequence operation theory. The CPLEX is used to solve the above model. Finally, taking a comprehensive energy system as an example, the impact of source load side carbon reduction measures on the system scheduling results under multiple time scales is analyzed.
Analysis and prediction of distribution network load characteristics based on data mining
Authors: Ye Peng , Yuan Yingzhi , Na Zheng , Liu Jun , Li Shiyu , Liu Anqi 
Published: December 2024

Abstract
Load forecasting helps the power department make annual, scheduling, and maintenance plans. In this paper, we take the distribution network of Shenyang as the research object, use the spectral clustering algorithm to cluster the load data, and analyze the correlation between the load and external factors through the correlation and gray correlation method. Moreover, we use the BO - TPE - XGBoost model for load forecasting and compare it with other methods. The results show that this method significantly improves the forecasting accuracy.
Distributed transaction method for multi-energy systems clusters considering uncertainties in photovoltaic power output
Authors: Huang Liuqiang , Huang Yan , Qin Lijuan , Deng Wenli , Hu Jianmin 
Published: December 2024

Abstract
In light of the emerging trend of distributed transactions within the multi-energy system(MES) cluster, this paper proposes a distributed transaction method for MES that takes into account the uncertainties in photovoltaic (PV) power output. This approach aims to achieve optimized resource scheduling within the MESs, as well as coordinated optimization of transactions between different MESs. Firstly, the uncertainties in PV power output within the MES are addressed using the distributionally robust chance constraint. Subsequently, the optimization problem of the MES cluster is decomposed using the alternating direction multiplier method, thereby establishing a distributed transaction model for the MES cluster that considers PV power output uncertainties. Finally, the case study demonstrates that the proposed model can balance the individual interests of each MES with the overall interests of the MES cluster. It effectively reduces the operating costs of the MESs and determines optimal operation strategies for them.
Decentralized optimization for multi-microgrid systems via enhanced concurrent alternating direction method of multipliers
Authors: Zheng Siyuan , Xiang Yejun , Wu Longdong , Sun Jingliao , Meng Jian , Huang Qifei 
Published: December 2024

Abstract
In microgrid systems, the diversity of power sources, limitations in network communication, and the growing emphasis on privacy protection for power generation equipment present significant challenges to traditional centralized dispatch methods. Within a system comprising multiple microgrids, a comprehensive assessment is conducted, taking into account the operational costs of conventional power generation units, the curtailment costs associated with renewable energy generation, and the depreciation costs of energy storage systems. Based on the distribution of power generation units and energy storage devices within the grid, a decentralized dynamic economic dispatch framework is established. Leveraging this groundwork, we have introduced a well-conceived and practical partitioning scheme specifically designed for the multi-microgrid landscape. An improved synchronous computational Alternating Direction Method of Multipliers (ADMM) is proposed, which, by exchanging only voltage phase information between adjacent areas during each iteration, enables parallel economic dispatch calculations across regions. This approach significantly enhances solution efficiency while ensuring overall optimization. Tested on a real-world microgrid case, the results validate the accuracy and practicality of the algorithm.
A coordinated control strategy for energy storage stations to suppress overvoltage in sending-end AC grid caused by DC blocking
Authors: Ma Runsheng , Han Dong , Li Yuyang , Zhang Wei , Lu Mengyu 
Published: December 2024

Abstract
A DC blocking event will cause a substantial quantity of reactive power injection into the sending-end AC grid, leading to overvoltage, which severely affects the secure and reliable functioning of the system. Synchronous condensers (SCs) offer the dual advantages of substantial capacity and rapid response speed, but their output target reactive power requires about 200-500 ms, much slower than energy storage stations. Therefore, this article introduces a coordinated control strategy for energy storage stations, grounded in the Karush-Kuhn-Tucker (KKT) conditions. The strategy in question is designed to optimize the reactive power margin, ensuring that the energy storage station’s total active power output remains steady while maximizing the reactive power it can absorb, as defined by the objective function. By solving the Lagrange equation in MATLAB, the objective value for the optimized energy storage unit’s output power is ascertained and subsequently allocated to individual energy storage units. In addition, the energy storage station, in conjunction with the SCs, jointly absorbs reactive power to mitigate overvoltage in the sending-end AC grid during DC blockages. Finally, simulations confirm the efficacy of the proposed coordinated control strategy.
Deadbeat predictive current control for high-speed permanent magnet synchronous motor based on extended state observer
Authors: Hua Qingyang , Mi Qianbao , Zhang Yi , Chen Fang 
Published: December 2024

Abstract
Addressing the serious issue of delays in the high-speed controlling area and the impact of motor parameter mismatches on current loop performance, this paper proposes a high-speed PMSM current control method based on an extended state observer (ESO). To improve the angle delay, a leading phase angle is introduced for compensation. Additionally, a one-step-ahead predictive compensation for time delay is included in the control method to reduce the time delay. The ESO is also employed to estimate electrical parameters and compensate for control errors, enhancing the robustness. The simulation validates the effectiveness of the method.
Automatic observation system for polar multi-parameter buoys based on SAILOR 4300
Authors: Zhao Jianglong , Dou Yinke 
Published: December 2024

Abstract
In recent years, with the gradual rise of global sea levels, the Arctic and Antarctic, as the largest freshwater reserves, have attracted increasing attention from scholars in various research fields. Among them, the melting of sea ice in the Arctic and subarctic regions is the most significant annual cycle change in the world. To monitor seawater quality, biological activity traces, and sea ice drift trajectories, an automatic monitoring device for multi-parameter observation of seawater was designed. The server and buoy processor programs are written in Python and can measure chlorophyll, dissolved oxygen, temperature, and salinity at a fixed horizontal depth for a long time. Meanwhile, we observe the activity status of underwater organisms at that point. We observe the movement trajectory of the sea ice where it is located throughout the entire work cycle. Due to the large amount of data transmission, SAILOR 4300 was used as the communication terminal for the system. A reliable transmission strategy was designed. In January 2024, the system underwent a one-week ice lake test. The interval between collection and transmission is 60 minutes. Based on the daily aging experiments of sensors and ice lake test data, it is shown that the system can be used for a long time in extremely low-temperature polar regions.
An improved fast filtering method based on target indication pre-calculation
Authors: Wang Baobao , Wan Shuaishuai 
Published: December 2024

Abstract
In order to improve the ability to track and monitor high-speed targets, an improved fast filtering method is proposed. Based on the traditional fast filtering of target indication pre-calculation, this paper makes full use of the target speed information in target indication data and constructs a non-stationary variable period extended dimension filtering method based on target indication pre-calculation, which enhances the fast-solving ability of high-speed maneuvering targets. Simulation results show that this method has better filtering performance compared with the traditional method.
Research on the application of load balancing strategy in IEC61850 communication of large-scale new energy monitoring system
Authors: Li Shaopeng , Zhang Ting , Hua Shuo , Pan Hongxiang , Zhang Xie , Shen Jian 
Published: December 2024

Abstract
This paper proposes an optimization scheme to achieve high throughput and stability of the system through efficient thread management and load-balancing strategies. Firstly, based on the IEC 61850 standard framework, a distributed architecture is constructed, which uses the advantages of multi-core processors for task distribution to improve data processing capabilities and system response speed. Secondly, in terms of thread management, prioritizing key operations ensures the timely processing of important data and reduces latency. At the same time, an asynchronous processing mechanism is introduced, so that the control and data can work in parallel, avoiding the occurrence of blockage. Then, the load-balancing strategy reasonably distributes the tasks to different processing nodes, avoiding the problem of single-point overload. Finally, the data caching mechanism and high-speed data bus are specially strengthened in the design to support the efficient transmission of large amounts of real-time data.
Optimization strategy for load demand response of microgrid clusters based on improved artificial hummingbird algorithm
Authors: Wang Zhenshang , Zhao Yuming , Wang Jing , He Shan , Tang Wenjun 
Published: December 2024

Abstract
As an emerging power system structure, microgrid clusters face significant challenges due to the increasing penetration rate of new energy sources such as photovoltaics, as well as intermittency and uncertainty in the distribution network system. This article proposes an optimization strategy for microgrid group load demand response based on an improved artificial hummingbird algorithm. Firstly, taking the interconnected microgrid group as the object, a load demand response model is established for the microgrid group, and the objective function and constraints of the microgrid group are determined. Then, an improved artificial hummingbird algorithm (mAHA) is proposed to solve the constructed model. Local Avoidance Operator (LEO) and Oppositional Learning (OBL) techniques are integrated to improve the basic Artificial Hummingbird Algorithm (AHA), accelerating convergence speed, enhancing solution quality, avoiding algorithm getting stuck in local optima, and thus better exploring the solution space. Ultimately, the improved artificial hummingbird algorithm is used to solve the load demand response model of microgrid clusters, to achieve lower economic costs for microgrid cluster operation.
Optimal DG hosting capacity evaluation method based on energy storage configuration and network reconfiguration strategy in power supply unit cluster
Authors: Li Hongjun , Ma Liang , Jiang Shigong , Qian Ruixin , Zhang Mingze , Shi Fangdi 
Published: December 2024

Abstract
For a single node in the power supply unit cluster, the effect of the node’s energy storage configuration capacity on improving the capacity of distributed power supply (DG) is analyzed, considering the energy storage access. Network reconfiguration is performed during operation to enhance DG capacity further. Firstly, a DG capacity evaluation model is constructed. The model maximizes DG capacity under various energy storage capacities for a single node, transforming it into a MILP model. Secondly, corresponding points of total cost and DG capacity under different storage capacities are obtained, and a piecewise linear interpolation method is used to plot the relationship curve. Thirdly, the optimal energy storage configuration and corresponding optimal DG capacity are determined by calculating the slope of the curve. Finally, the proposed model and method are verified on the IEEE-33 node system.
Analysis of the effect of active power threshold on dynamic metering of energy meters
Authors: Zhang Xinhui , Lu Da , Wang Chunyan , Li Helong 
Published: December 2024

Abstract
With the high proportion of new energy and power electronic equipment access in the construction of new power systems, the dynamic volatility of the grid signal is stronger, which poses a serious challenge to accurate metering. To address this problem, this paper starts with the analysis of the electric energy metering algorithm principle. Firstly, the measurement characteristics of the Moving average algorithm and the Non-overlapping algorithm are compared. Secondly, on the basis of studying the steady-state signal metrology power metering error of the two algorithms when there is an active power threshold, the metrology ability of the two algorithms to dynamic signal is further analyzed. The conclusion is drawn that the threshold will cause the metrology power metering error of the moving average algorithm. The non-overlapping algorithm has a certain probability of power metering error. Finally, by designing different input signals, the moving average and non-overlapping algorithms are tested, respectively, to verify the effectiveness of the analysis. The research results of this paper can provide ideas for the research and analysis of dynamic metering algorithms of energy meters.
Development and testing of a remote calibration device for the temperature field of environmental testing equipment
Authors: Xiong Zhichun , Ling Yancui , Chen Xu 
Published: December 2024

Abstract
Temperature is one of the important parameters for the calibration of environmental testing equipment. Due to its special working requirements and large volume and weight, the demand for on-site inspection and calibration of environmental testing equipment has always been high. Conducting research on remote calibration devices for temperature fields in environmental testing equipment is beneficial for improving the testing efficiency of environmental temperature and humidity, reducing the workload of testing personnel, and further reducing customer testing costs. By using ANT Wireless technology and using SHT3X temperature and humidity sensors to create a temperature field calibration device for environmental testing equipment, the above functions can be achieved. After testing, the maximum transmission distance of a single node can reach 70 meters, and the maximum networking distance between multiple nodes can exceed 1,000 meters. It can adapt to high and low-temperature impact tests at -20°C~60°C, and the response speed of temperature and humidity sensors is slightly slower than traditional temperature measurement thermocouples. It is suitable for calibration and detection of environmental testing equipment with good insulation performance.