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Fluctuation Classification and Feature Factor Extraction to Forecast Very Short-Term Photovoltaic Output powers

CSEE Journal of power and Energy systems 2025年第2期11卷 661-670页

作者： Mao Yang Xiaoxuan Shen Dawei Huang Xin Su Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin 132012China

In recent years, a spurt of photovoltaic power generation has brought certain impact on stability of the power system, which puts forward higher requirements on accuracy of photovoltaic power prediction. Therefore, this paper proposes a hybrid power prediction model based on fluctuation classification and feature factor extraction. First, based on fluctuation characteristics of photovoltaic power, fluctuation classification is applied to forecast power before the day, and weather is divided into complex fluctuation types and simple types. Then, parallel factor algorithm is used to reduce prediction model redundancy, which can reduce high-dimensional numerical weather prediction feature matrix to extract relevant features. Finally, the Long Short-Term Memory (LSTM) deep learning model is used to forecast very short-term photovoltaic power. The proposed hybrid model is compared with other methods, and photovoltaic data from several sites are selected for comparison and validation in this paper. simulation results show that very short-term prediction method of photovoltaic power proposed in this paper can significantly improve prediction accuracy.

关键词： Deep neural networks fluctuation classification PARAFAC photovoltaic generation very short-term forecasting

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Reactive power Optimization Model of Active Distribution Network with New Energy and Electric Vehicles

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Energy Engineering 2025年第3期122卷 985-1003页

作者： Chenxu Wang Jing Bian Rui Yuan Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control&Renewable Energy TechnologyMinistry of EducationJilin132011China

Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is ***,the k-medoids clustering algorithm is used to divide the reduced power scene into ***,the discrete variables and continuous variables are optimized in the same period of ***,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging *** to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution *** simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.

关键词： Active distribution network new energy electric vehicles dynamic reactive power optimization kmedoids clustering hybrid optimization algorithm

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Bipolar Direct AC/AC Conversion-based Dual-bus Parallel Supply system and Its Flexible Regulation Characteristics

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Protection and control of Modern power systems 2025年第3期10卷 114-124页

作者： Wang, Yibo Liu, Yu Liu, Chuang Cai, Guowei Zhang, Xinyi Liu, Kaipu Wang, Yuan Liu, Chen Du, Zhanhui Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Jilin132012 China

In the context of increasing demand for flexibility and controllability in distribution networks, this paper proposes a dual-bus parallel supply (DBPS) system based on bipolar direct AC/AC conversion. First, the topology of the DBPS system, which is composed of both conventional and flexible bus ports, is described. Then, through analyzing the principles of the DBPS system, the voltage flexible regulation range is obtained, and its superiority over a topological reciprocity system is achieved. Then, a control strategy for the DBPS system is proposed based on the theory of power flow regulation of distribution ring networks and the principles of flexible bus regulation of the DBPS system. Finally, simulation analyses on flexible control scenarios in different networking modes of the DBPS system verify the correctness and validity of the proposed theory. © 2019 power system Protection and control Press.

关键词： Electric power system control

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An equivalent modeling method for integrated water-wind-solar systems based on sparrow search algorithm

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Energy Informatics 2025年第1期8卷 1-16页

作者： Lu, Yuanhong Zhang, Jie Zhang, Jingyue Huang, Libin Guo, Haiping Hu, Binjiang Guo, Tianyu State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou510663 China National Energy Power Grid Technology R & D Centre Guangzhou510663 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou510663 China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou510663 China

In the context of extensive integration of renewable energy sources into the electrical grid, the grid's fault transient behaviors have undergone significant changes. However, conventional single-unit equivalent models fail to accurately capture the fault transient responses of combined wind-solar-hydro power stations and often require substantial computational resources, leading to reduced simulation efficiency. This study proposes a cluster-based equivalent modeling approach for hybrid wind-solar-hydro power plants using the Sparrow Search Algorithm. key factors influencing fault characteristics, including the distance to the Point of Common Coupling, DC-side current-limiting measures, irradiance levels, water flow rates, wind speeds, and reactive power at the outlet, are identified and used to construct a transient model. Euclidean distances are computed for these factors, and initial clustering centers for wind turbines are determined using an improved max–min distance technique. These factors and clustering centers serve as the training dataset to establish the clustering equivalent model. simulation results, conducted on the MATLAB2022 platform, demonstrate that the SSA-based model outperforms the single-unit equivalent model by over 150 times in terms of accuracy. Additionally, the SSA-based model achieves a delay time, defined as the time required to compute the system's transient response after a fault, of less than 5 ms, which is less than one-twentieth of the delay time of the single-unit equivalent model. These improvements highlight the model's ability to accurately capture dynamic power responses under various disturbances, making it highly suitable for real-time applications in hybrid renewable energy systems. © The Author(s) 2025.

关键词： MATLAB

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The electromagnetic transient simulation acceleration algorithm based on delay mitigation of dynamic critical paths

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Energy Informatics 2025年第1期8卷 1-12页

作者： Guo, Qi Lu, Yuanhong Zhang, Jie Zhang, Jingyue Huang, Libin Guo, Haiping Guo, Tianyu Tu, Liang State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou510663 China National Energy Power Grid Technology R & D Centre Guangzhou510663 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou510663 China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou510663 China

The task scheduling problem based on directed acyclic graphs (DAGs) has been proven to be NP-complete in general cases or under certain restrictions. In this paper, building upon existing scheduling algorithms, we introduce a static task scheduling algorithm based on directed acyclic graphs. By incorporating the proportion of task transmission delay as a guiding metric in the optimization process, processors can be prioritized for tasks with high latency, thereby improving computational efficiency. We first validate the theoretical feasibility of the algorithm using a theoretical case study and illustrate the algorithmic effectiveness using two real case studies, direct current (DC) model and alternating current (AC) model respectively. The research indicates that the scheduling algorithm proposed in this paper achieves an average scheduling length improvement of over 1.2% compared to the Heterogeneous Earliest-Finish-Time algorithm (HEFT) in topologies with high latency tasks. Additionally, the experiments show that the HEFT algorithm consumes 39.85us and the EMT-DM algorithm consumes 38.29us during simulation using DC, and the HEFT algorithm consumes 31.23us and the EMT-DM algorithm consumes 26.51us during simulation using AC, both of which are improved compared to the HEFT algorithm. © The Author(s) 2025.

关键词： Flow graphs

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GD-YOLO:A Network with Gather and Distribution Mechanism for Infrared Image Detection of Electrical Equipment

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Computers, Materials & Continua 2025年第4期83卷 897-915页

作者： Junpeng Wu Xingfan Jiang Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China School of Electrical Engineering Northeast Electric Power UniversityJilin132012China

As technologies related to power equipment fault diagnosis and infrared temperature measurement continue to advance,the classification and identification of infrared temperature measurement images have become crucial in effective intelligent fault diagnosis of various electrical *** response to the increasing demand for sufficient feature fusion in current real-time detection and low detection accuracy in existing networks for Substation fault diagnosis,we introduce an innovative method known as Gather and Distribution Mechanism-You Only Look Once(GD-YOLO).Firstly,a partial convolution group is designed based on different convolution *** combine the partial convolution group with deep convolution to propose a new Grouped Channel-wise Spatial Convolution(GCSConv)that compensates for the information loss caused by spatial channel ***,the Gather and Distribute Mechanism,which addresses the fusion problem of different dimensional features,has been implemented by aligning and sharing information through aggregation and distribution ***,considering the limitations in current bounding box regression and the imbalance between complex and simple samples,Maximum Possible Distance Intersection over Union(MPDIoU)and Adaptive SlideLoss is incorporated into the loss function,allowing samples near the Intersection over Union(IoU)to receive more attention through the dynamic variation of the mean Intersection over *** GD-YOLO algorithm can surpass YOLOv5,YOLOv7,and YOLOv8 in infrared image detection for electrical equipment,achieving a mean Average Precision(mAP)of 88.9%,with accuracy improvements of 3.7%,4.3%,and 3.1%,***,the model delivers a frame rate of 48 FPS,which aligns with the precision and velocity criteria necessary for the detection of infrared images in power equipment.

关键词： Infrared image detection aggregation and distribution mechanism sample imbalance strategy lightweight structure

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Online Optimization to Suppress the Grid-Injected power Deviation of Wind Farms with Battery-Hydrogen Hybrid Energy Storage systems

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Energy Engineering 2025年第4期122卷 1403-1424页

作者： Min Liu Qiliang Wu Zhixin Li Bo Zhao Leiqi Zhang Junhui Li Xingxu Zhu State Grid Zhejiang Electric Power Co. Ltd.Electric Power Research InstituteHangzhou310014China Key Laboratory of Modern Power System Simulation Control and Green Power New Technology of the Ministry of Education Northeast Electric Power UniversityJilin132012China

To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is ***,considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage,an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage ***,an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with satisfying the operational constraints of hydrogen storage and ***,utilizing the online measurement of the energy states of hydrogen storage and batteries,an online optimization strategy based on measurement feedback is *** study results show:before and after smoothing the fluctuations in wind power,the time when the power exceeded the upper and lower limits of the grid-injected power accounted for 24.1%and 1.45%of the total time,respectively,the proposed strategy can effectively keep the grid-injected power deviations of wind farms within the allowable *** storage and batteries respectively undertake long-term and short-term charge/discharge tasks,effectively reducing charge/discharge losses of the Battery-hydrogen hybrid energy storage systems and improving its operational efficiency.

关键词： Battery-hydrogen hybrid energy storage systems grid-injected power deviations measurement feedback online optimization energy states

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Investigating Black-Box Model for Wind power Forecasting Using Local Interpretable Model-Agnostic Explanations Algorithm

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CSEE Journal of power and Energy systems 2025年第1期11卷 227-242页

作者： Mao Yang Chuanyu Xu Yuying Bai Miaomiao Ma Xin Su Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Daqing Power Industry Bureau Daqing 163000China

Wind power forecasting(WPF)is important for safe,stable,and reliable integration of new energy technologies into power *** learning(ML)algorithms have recently attracted increasing attention in the field of ***,opaque decisions and lack of trustworthiness of black-box models for WPF could cause scheduling *** study develops a method for identifying risky models in practical applications and avoiding the ***,a local interpretable model-agnostic explanations algorithm is introduced and improved for WPF model *** that basis,a novel index is presented to quantify the level at which neural networks or other black-box models can trust features involved in ***,by revealing the operational mechanism for local samples,human interpretability of the black-box model is examined under different accuracies,time horizons,and *** interpretability provides a basis for several technical routes for WPF from the viewpoint of the forecasting ***,further improvements in accuracy of WPF are explored by evaluating possibilities of using interpretable ML models that use multi-horizons global trust modeling and multi-seasons interpretable feature selection *** results from a wind farm in China show that error can be robustly reduced.

关键词： Black-box model correlation analysis feature trust index local interpretability local interpretable modelagnostic explanations(LIME) wind power forecasting

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Effects of Corona Discharge from the Grounding Tip on Charge Evolution of Wall Bushing

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IEEE Transactions on power Delivery 2025年第3期40卷 1682-1693页

作者： Bai, Zheng Zhou, Yuanxiang Zhang, Yunxiao Huang, Xin Xie, Xiongjie Liu, Taiwei Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing100084 China Electric Power Research Institute State Key Laboratory of Power Grid Environmental Protection Wuhan430204 China

Manufacturers consider that the grounding tip near the wall bushing flange is a potentially important factor in several sheath perforation accidents. Taking a ±100 kV true type SF6 gas-insulated bushing as a typical wall bushing, this paper tests the impact of the nearby grounding tip on the charge accumulation. Based on the experiment results, we propose the three-dimensional nonlinear conduction model to unravel the charge accumulation process and the three-dimensional corona ion migration model to clarify the corona process. It is concluded that the consumption of gas ions leads to the nonlinear charge relaxation process. When the corona of grounding tip incepts, numerous ions are generated, forming an "overcharge" phenomenon. The electric field at the insulator-sheds interface and the SF6-insulator interface increases compared to the normal condition, with non-uniform distribution along the circumferential direction. Material inhomogeneity amplifies electric field distortion and creates insulation weaknesses, making insulation aging more likely and potentially leading to a slowly developing electrical tree breakdown process. The length of the needle tip affects the duration of the corona effect;an excessively long needle tip can cause a sustained corona discharge. This research provides a foundation for bushing accidents analysis and operation reliability improvement. © 1986-2012 IEEE.

关键词： Bushings

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Monthly Reduced Time-Period Scheduling of Thermal Generators and Energy Storage Considering Daily Minimum Chargeable Energy of Energy Storage

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Energy Engineering 2025年第4期122卷 1469-1489页

作者： Xingxu Zhu Shiye Wang Gangui Yan Junhui Li Hongda Dong Chenggang Li Key Laboratory of Modern Power System Simulation Control and Green Power New Technology of the Ministry of Education Northeast Electric Power UniversityJilin132012China State Grid Jilin Electric Power Co. Ltd.Electric Power Science Research InstituteJilin130021China

To address the excessive complexity of monthly scheduling and the impact of uncertain net load on the chargeable energy of storage,a reduced time-period monthly scheduling model for thermal generators and energy storage,incorporating daily minimum chargeable energy constraints,was ***,considering the variations in the frequency of unit start-ups and shutdowns under different levels of net load fluctuation,a method was proposed to reduce decision time periods for unit start-up and shut-down *** approach,based on the characteristics of net load fluctuations,minimizes the decision variables of units,thereby simplifying the monthly ***,the relationship between energy storage charging and discharging power,net load,and the total maximum/minimum output of units was *** on this,daily minimum chargeable energy constraints were established to ensure the energy storage system meets charging requirements under extreme net load ***,taking into account the operational costs of thermal generators and energy storage,load loss costs,and operational constraints,the reduced time-period monthly schedulingmodel was *** studies demonstrate that the proposedmethod effectively generates economical monthly operation plans for thermal generators and energy storage,significantly reduces model solution time,and satisfies the charging requirements of energy storage under extreme net load conditions.

关键词： Monthly scheduling thermal generators energy storage daily minimum chargeable energy decision time-period reduction unit start-up and shut-down unit commitment renewable energy

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