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Smart Grid and Artificial Intelligence (SGAI), International Conference on

作者： Xiuyu Yang Zekun Fan Almasbek Shakenbek Baoyu Di Chongbi Li Yi Wang Key Laboratory of Modern Power System Simulation Control and New Green Energy Technology of Ministry of Education Northeasst Electric Power University Jilin China State Grid Xinjiang Electric Power Co. Ltd. State Grid Xinjiang Electric Power Co. Ltd. Electric Power Research Institute Urumqi China

ISBN: (数字)9798331518806

ISBN: (纸本)9798331518813

The large-scale access of renewable energy to the power grid leads to a sharp increase in the demand for power system regulation capacity. In order to solve this problem, this paper explores the mechanism of supply and demand balance of power system regulation capacity, analyzes the transmission characteristics of regulation capacity, and proposes the adequacy index of node regulation capacity and the adequacy index of network transmission regulation capacity. The Garver-6 node system is used to verify the effectiveness and practicability of the proposed method. The example shows that the proposed evaluation method can accurately identify the weak links of regulation ability and clarify the causes of insufficient regulation ability.

关键词： Renewable energy sources Supply and demand power transmission lines Evaluation models Regulation Smart grids Planning Artificial intelligence Load flow Capacity planning

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FDCA-DSTGCN: A Wind Farm Cluster power Day-ahead Prediction Model Based on Frequency Domain Information Gain and Dynamic Trend Sensing

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IEEE Transactions on Sustainable energy 2025年

作者： Yang, Mao Niu, Jiajun Wang, Bo Huang, Dawei Su, Xin Ma, Chenglian Ministry of Education Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin132012 China China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems Beijing100912 China

Accurate wind farm cluster power prediction (WFCPP) is of vital significance for new power systems with large-scale wind power integration. The current WFCPP modeling method ignores the important role of wind direction and frequency domain information, resulting in insufficient use of spatial information and difficult to improve the prediction accuracy. In order to solve the above problems, a day-ahead power prediction model for wind farm cluster power is proposed based on information gain in frequency domain and dynamic trend sensing. Firstly, a cluster division method based on graph theory and progressive fusion of multiple information is proposed, and a virtual information node is set up. Secondly, a method to identify prevailing wind direction under time window is proposed for subsets, and a dynamic weighted directed graph structure is designed based on prevailing wind direction and wind speed. Thirdly, a dynamic spatio-temporal graph convolutional network model with frequency domain gain channel attention mechanism (FDCA-DSTGCN) is proposed to integrate the above information and complete the prediction. Finally, the proposed method is applied to a wind farm cluster in Inner Mongolia of China. Compared with the existing and traditional prediction methods, the normalized root mean square error of the proposed method is reduced by 1.13% -2.15%, which verifies the effectiveness of the proposed method. © 2010-2012 IEEE.

关键词： Mean square error

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The Day-ahead Scenario Generation Method for new energy Based on an Improved Conditional Generative Diffusion Model

arXiv

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arXiv 2025年

作者： Wang, Changgang Liu, Wei Cao, Yu Liang, Dong Li, Yang Mo, Jingshan Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin Province Jilin132012 China School of Electrical Engineering Northeast Electric Power University Jilin Province Jilin132012 China Jilin Power Supply Company Substation Secondary Maintenance Center Jilin Province Jilin132012 China

In the context of the rising share of new energy generation, accurately generating new energy output scenarios is crucial for day-ahead power system scheduling. Deep learning-based scenario generation methods can address this need, but their black-box nature raises concerns about interpretability. To tackle this issue, this paper introduces a method for day-ahead new energy scenario generation based on an improved conditional generative diffusion model. This method is built on the theoretical framework of Markov chains and variational inference. It first transforms historical data into pure noise through a diffusion process, then uses conditional information to guide the denoising process, ultimately generating scenarios that satisfy the conditional distribution. Additionally, the noise table is improved to a cosine form, enhancing the quality of the generated scenarios. When applied to actual wind and solar output data, the results demonstrate that this method effectively generates new energy output scenarios with good adaptability. © 2025, CC BY-NC-ND.

关键词： Markov chains

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Fuzzy optimal scheduling of hydrogen-integrated energy systems with uncertainties of renewable generation considering hydrogen equipment under multiple conditions

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Applied energy 2025年 393卷

作者： Song, Jianzhao Wang, Na Zhang, Zhong Wu, Hao Ding, Yi Pan, Qingze Pan, Xingzuo Shui, Siyuan Chen, Haipeng Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Department of Electrical Engineering Northeast Electric Power University Jilin132012 China Gansu Branch of Luneng New Energy Group Co. Ltd. Lanzhou730000 China Lanzhou Power Supply Company State Grid Gansu Electric Power Co. Ltd. Lanzhou730000 China TBEA Shenyang Transformer Group Co. Ltd. Shenyang110144 China Northeast Electric Power University Jilin132012 China

Developing hydrogen-integrated energy systems (HIES) represents a cutting-edge strategy for harnessing renewable energy (RE). However, the inherent unpredictability and variability of RE significantly increase the operational uncertainty of HIES, which leads to severe energy curtailment issues when HIES integrates large-scale RE, necessitating greater operational flexibility in the system. To address the challenges, this paper proposes a fuzzy optimal scheduling approach for HIES that considers the hydrogen equipment under multiple operating conditions. The analysis begins by examining the operational mechanisms of hydrogen equipment. Subsequently, a multi-conditions model is developed for electrolyzers, while a reserve model is established for hydrogen fuel cells. Furthermore, the fuzzy chance constraint (FCC) is employed to quantify the uncertainty of RE generation. An integrated demand response mechanism is implemented, incorporating human thermal comfort and building thermal inertia. Finally, a fuzzy optimization scheduling model for HIES is constructed to minimize the total operating costs. The crisp equivalent of FCC is derived to solve this model, thereby transforming the scheduling model based on fuzzy chance-constrained programming into a solvable mixed-integer programming model. The simulation results indicate that the proposed scheduling method can reduce the overall costs of the HIES by 17.98 % and increase the RE accommodation rate by 19.67 %, validating the effectiveness of the method in enhancing the operational flexibility of the HIES. In addition, this study achieves a balance between economic efficiency and reliability, offering a better economy, lower energy curtailment rates, and faster decision-making times compared to robust optimization, scenario analysis, and other common fuzzy optimization methods. © 2025

关键词： Risk perception

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Mobile Hybrid Distribution Transformer Deployment Strategy Based on Spatial Coordinate system Mapping Optimization 11

Mobile Hybrid Distribution Transformer Deployment Strategy B...

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11th China International Conference on Electricity Distribution, CICED 2024

作者： Wang, Yibo Liu, Kaipu Liu, Chen Liu, Yu Du, Zhanhui Wang, Yuan Northeast Electric Power University The Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Jilin China

ISBN: (纸本)9798350368345

Under the background of 'double carbon', the power system is facing green change, and the distribution network is facing the challenge of distributed generation and diversified load. Traditional distribution transformers are unable to cope with local load peaks and sudden load growth. In order to cope with the problem of heavy overload caused by seasonal load, mobile hybrid distribution transformer (MHDT) has gradually attracted attention as an innovative solution. In this paper, the deployment strategy of MHDT is discussed, and an optimization method based on spatial coordinate system mapping is proposed to reduce the amount of calculation and improve the computational efficiency. Through the practical application case of an agricultural irrigation area in Jilin Province, the actual effect of this method in solving the problem of transformer heavy overload is verified. The results show that MHDT can effectively improve flexibility response ability of distribution system. © 2024 IEEE.

关键词： Distribution transformers

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Analysis of Subsynchronous Torsional Vibration of Wind-Thermal Bundling Delivery system via LCC-HVDC 6

Analysis of Subsynchronous Torsional Vibration of Wind-Therm...

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6th IEEE International Electrical and energy Conference, CIEEC 2023

作者： Zhao, Yue Yan, Gangui Wang, Zhenyang Ren, Shuang Wang, Dazhong Guo, Jianyu Northeast Electric Power University Key Laboratory of Modern Power System Simulation Control and Green Power Technology Dept. Ministry of Education Jilin China

ISBN: (纸本)9798350346671

Recently, Wind-thermal bundled transmission via LCC-HVDC has become the main way of wind energy development and utilization in my country at present and in the future. The complex interaction between wind turbines, thermal power units, and LCC-HVDC needs to be further studied. In this paper, aiming at the direct-drive wind turbine group, thermal power unit and HVDC, the linearization model of the system is established, and the interactive coupling relationship between the connected equipment and the electrical damping of the thermal power unit is analyzed, and the mechanism of torsional vibration of thermal power unit shafting caused by wind-thermal bundling via LCC-HVDC is studied. mechanism. Based on the complex torque coefficient method, the influence of factors such as wind speed, control parameters, HVDC transmission power and control parameters on the electrical damping coefficient of thermal power units is studied. Finally, a time-domain simulation model is built in PSCAD/EMTDC, and the effectiveness of the electrical damping coefficient analysis results is verified through time-domain simulation and time-frequency analysis. © 2023 IEEE.

关键词： Wind

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FAULT DIAGNOSIS METHOD FOR DC DISTRIBUTION NETWORKS BASED ON SEMITENSOR PRODUCT BAYESIAN NETWORKS 6

FAULT DIAGNOSIS METHOD FOR DC DISTRIBUTION NETWORKS BASED ON...

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6th International Scientific and Technical Conference Relay Protection and Automation, RPA 2023

作者： Wang, He Li, Shiqiang Yu, Huanan Bian, Jing Wei, Bo Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China

ISBN: (纸本)9798350382334

关键词： Bayesian networks

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Stochastic power Flow Distributed Algorithm for Distribution Network Based on Scenario Equivalence Between Regions

Stochastic Power Flow Distributed Algorithm for Distribution...

引用

2023 International Conference on power system technology, powerCon 2023

作者： Jing, Zhibin Sun, Jiacheng Hao, Qianpeng Li, Qiang Ren, Jie Zhang, Ye Zhao, Hanjie Li, Junhui Li, Cuiping Inner Mongolia Power Company Limited Dispatch Control Branch Hohhot China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin China

ISBN: (纸本)9798350300222

A distributed stochastic power flow algorithm for distribution network based on inter-region scenario equivalence is proposed for the problem that the power injection of each node needs to be simulated with a large number of samples in the distribution network stochastic power flow algorithm, thus causing low computational efficiency. Firstly, the distribution network is divided into a backbone region and several sub-regions according to its radial structure characteristics, and the sampled power samples are partitioned;secondly, based on the inter-region power flow coupling relationship, the inter-region power flow action is replaced with the effect on the boundary quantity;then, a scenario equivalence method is proposed to merge the power scenarios that cause the same boundary injected power and boundary voltage. Finally, a distributed algorithm for distribution network stochastic currents is designed, and each region can complete the distributed solution of distribution network stochastic currents through the exchange of boundary equivalence scenario information and internal calculation, and the accuracy and effectiveness of the proposed method in reducing time are verified in the IEEE123 node system calculation example. © 2023 IEEE.

关键词： Electric power distribution

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Dynamic Behavior of Suspended Bubbles in Insulating Oil Correlation with Flow Field Distribution 4th

Dynamic Behavior of Suspended Bubbles in Insulating Oil Corr...

引用

4th International Symposium on Insulation and Discharge Computation for power Equipment, IDCOMPU 2023

作者： Zhang, Ning Hao, Jian Liu, Shili Zhang, Junyi Chen, Houhe Liao, Ruijin Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing400044 China

ISBN: (纸本)9789819974122

In recent years, arcing faults inside large oil-immersed power transformers have been frequent. Suspended bubbles, as the main product of high temperature, high humidity, material aging and cracking gas production inside transformers, are one of the main causes of arcing inside transformers. However, due to the complex structure of the oil channel and the large fluctuation of the internal flow field distribution, the resulting bubble morphology evolution and movement law is not clear. In this paper, the influence of the initial position of bubbles and the relative position between bubbles on the flow field distribution is fully considered, and the dynamic behavior of suspended bubbles in oil under two fluid forms of natural oil circulation and forced oil circulation is simulated and studied by combining laminar and turbulent flow models and bubble force control equations, and the correlation mechanism between suspended bubbles and flow field distribution characteristics is analyzed. The simulation results show that the flow field in the laminar state affects the bubble aggregation and trajectory, while the turbulent state affects the bubble distortion and motion time, and a reasonable model in the simulation of bubble dynamic behavior is more beneficial to improve the simulation accuracy. © Beijing Paike Culture Commu. Co., Ltd 2024.

关键词： Flow fields

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Large-Scale Multi-Object Rearrangement

Large-Scale Multi-Object Rearrangement

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Huang, Eric Jia, Zhenzhong Mason, Matthew T. State Grid Liaoning Electric Power Co Ltd Shenyang China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

ISBN: (纸本)9781538660263

This paper describes a new robotic tabletop rearrangement system, and presents experimental results. The tasks involve rearranging as many as 30 to 100 blocks, sometimes packed with a density of up to 40%. The high packing factor forces the system to push several objects at a time, making accurate simulation difficult, if not impossible. Nonetheless, the system achieves goals specifying the pose of every object, with an average precision of +/- 1 mm and +/- 2 degrees. The system searches through policy rollouts of simulated pushing actions, using an Iterated Local Search technique to escape local minima. In real world execution, the system executes just one action from a policy, then uses a vision system to update the estimated task state, and replans. The system accepts a fully general description of task goals, which means it can solve the singulation and separation problems addressed in prior work, but can also solve sorting problems and spell out words, among other things. The paper includes examples of several solved problems, statistical analysis of the system's behavior on different types of problems, and some discussion of limitations, insights, and future work.

关键词： Planning Task analysis Grasping Robots Annealing Trajectory Markov processes

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