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Reactive power Optimization Model of Active Distribution Network with new energy and Electric Vehicles

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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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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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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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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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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Stackelberg Game for Bilateral Transactions between energy Storage and Wind Farms Considering the Day-Ahead Electricity Market

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energy Engineering 2025年第5期122卷 1645-1668页

作者： Xingxu Zhu Guiqing Zhao Gangui Yan JunhuiLi Hongda Dong Chenggang Li Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin132012China Electric Power Research Institute of State Grid Jilin Electric Power Co. Ltd.Jilin130021China

The participation of wind farms in the former energymarket faces challenges such as power fluctuations and energy storage construction *** this end,this paper proposes a joint energy storage operation scheme for multiple wind farms based on a leasingmodel,which assistswind farms in bidding for participation in the former energy market through leasing services,thereby enhancing energy storage efficiency and maximizing economic *** this paper,based on theWeibull probability distribution to portray the uncertainty of wind power,and considering the lifetime capacity loss caused by charging and discharging of energy storage,we construct a bilateral transaction model aiming at maximizing the multi-objective revenue of wind farms and shared energy *** trading strategy is designed based on the Stackelberg game framework and solved jointly by the improved genetic algorithm and interior *** exploring the effects of different lease price intervals on the overall systemperformance,and analyzing the systemstate undermultiple charging and discharging *** results show that a reasonable lease price range can significantly improve the energy storage system utilization and wind *** new ideas to enhance the economic benefits of wind farms and promote the application of shared energy storage,and promotes the wide application of shared energy storage systems.

关键词： energy storage wind power uncertainty energy market stackelberg game leasing price

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Master-Slave Game Strategy for Electric Heating Load Group Considering Differences of Heterogeneous Household Types and Aggregation Structure

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Dianli Xitong Zidonghua/Automation of Electric power systems 2025年第10期49卷 58-66页

作者： Yang, Mao Wang, Jinxin Fang, Guozhong Zhu, Yidan Wang, Yuxin Su, Xin Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Northeast Branch of State Grid Corporation of China Shenyang110179 China

The regulation capability of the new power system dominated by renewable energy at the source side is gradually deteriorating. Exploiting the load-side regulation potential to participate in demand response has become an important approach to enhance grid regulation capacity. Firstly, taking distributed residential electric heating clusters as the research object, a dynamic model of temperature-varying power is established for electric heating rooms based on the building thermodynamics theory. Secondly, the impacts of household type differences and aggregated household proportions on the regulation capability of heating load clusters are investigated. A refined aggregation model for heating load clusters considering the differences of heterogeneous household types and aggregation structure is established, with adjustable electricity quantified as an indicator to measure the regulation potential of heating load clusters. Then, a master-slave game model is constructed with the load aggregator (LA) as the leader and cluster users as followers. The quantified adjustable electricity of load clusters is incorporated into the game model as flexible resources to participate in demand response. The upper-level game model establishes an LA pricing model to formulate electricity scheduling plans and optimal heating electricity prices within the system, while the lower-level develops a user payment cost model where users determine their heating schedules based on the electricity prices. Finally, case studies verify that the proposed game model can effectively stimulate the demand response potential of users with the differences of heterogeneous household type, achieving economic benefits for both LA and users. © 2025 Automation of Electric power systems Press. All rights reserved.

关键词： Cooling

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Analysis of Frequency Dynamic Distribution Characteristics in Chain-structured power system with Renewable energy Integration

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Dianli Xitong Zidonghua/Automation of Electric power systems 2025年第10期49卷 49-57页

作者： An, Jun Shi, Yan Cao, Shuai Zhou, Yibo Li, Kexin Zhang, Wanxiang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Northeast Branch of State Grid Corporation of China Shenyang110179 China

The integration of renewable energy generation, represented by wind power, into the power system has a significant impact on frequency security, and the characteristics of frequency distribution have gradually become a focal point of attention. To study the influence of wind power integration into multi-machine systems on frequency distribution characteristics, based on the frequency response characteristics of the"grid, source, and load"sides, this paper constructs an analytical model of the frequency response distribution characteristics of a multi-machine system with wind power, and analyzes the impact mechanism of wind power integration on the frequency distribution characteristics. Then a multi-dimensional quantification index system is developed to describe the relative dispersion and absolute differences in frequency response. Next, the validity of the mechanism model is verified using a simple chain-structured power system with"generation-transmission-reception", and the influence rules of electrical distance, wind power integration location, and disturbance location on the frequency distribution characteristic indices are analyzed. Finally, the influence rules of distribution characteristics are analyzed and verified in an actual large-scale power system with a high proportion of renewable energy. © 2025 Automation of Electric power systems Press. All rights reserved.

关键词： Wind power integration

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Adaptive Adjustment Method for Grid-forming energy Storage Parameters Based on Buffer Functions and Damping Switching

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Dianli Xitong Zidonghua/Automation of Electric power systems 2025年第10期49卷 77-86页

作者： Cui, Yang Ma, Boyu Dai, Hanyang Ma, Xin Zhao, Yuting Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China China Electric Power Research Institute Beijing100192 China Electric Power Research Institute of State Grid Ningxia Electric Power Ltd. Co. Yinchuan750002 China

In the development tendency of high penetration of renewable energy and power electronic devices in new power systems, the grid-forming control technology for renewable energy integration mitigates the system stability issues caused by insufficient inertia and damping. However, it also reduces the dynamic regulation performance of the system. This paper proposes an adaptive adjustment method for grid-forming energy storage parameters based on buffer functions and steady-state/transient-state damping switching, to improve the dynamic regulation performance of the system. Firstly, the buffer functions are used in inertia adjustment to enhance the regulation smoothness of the system. Secondly, a steady-state/transient-state damping switching link is introduced in the damping adjustment to reduce the steady-state error of active power output during the frequency reduction process. Thirdly, the fuzzy control is employed to introduce correction terms for inertia and damping, and the stability of the proposed method is analyzed. Finally, simulations validate the effectiveness of the proposed method in enhancing small-signal stability and power response dynamic performance of the system. © 2025 Automation of Electric power systems Press. All rights reserved.

关键词： Electric power transmission networks

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A Short-Term power Prediction Method for Wind Farm Cluster Based on Time Dynamic Graph Network and Improved Transformer Model

A Short-Term Power Prediction Method for Wind Farm Cluster B...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Chao Han Zihang Chen Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China Jiangmen Power Supply Bureau of Guangdong Power Grid Co. Ltd Jiangmen China

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

In recent years, wind power has gradually replaced thermal power as the main source of new energy generation. Wind power prediction in advance can help formulate scheduling strategies and improve the stability of the power system. With the advent of the Industry 4.0 and the widespread application of artificial intelligence technology, artificial algorithms have been extensively used in the field of wind power prediction. To further explore the spatiotemporal correlation of every wind farm in the wind farm cluster, a temporal dynamic graph network is used to divide the wind farm farm into several sub-clusters. Then, the KAN-BiLSTM-Transformer algorithm is used to predict wind power of each wind sub-cluster. Finally, the wind power of each sub-cluster is added to attain the final predicted power of the wind farm cluster. After verification, the RMSE and MAE of the proposed method is 0.06849 and 0.05805 respectively, with an accuracy of 93.15%, which is superior to the compared algorithms. Proposed method can provide more accurate prediction results.

关键词： Accuracy Heuristic algorithms Clustering algorithms Wind power generation Wind farms Predictive models Prediction algorithms Transformers Spatiotemporal phenomena Wind forecasting

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