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SSRN 2023年

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

The accuracy of Direct Current (DC) distribution network fault location for a single electrical or switching quantity fault information is difficult to meet the requirements. This paper proposes a fault location method of DC distribution network based on multivariate information fusion. Firstly, the compressed sensing algorithm is used to reconstruct the fault transient electrical data to obtain the sparse characteristics of the high-frequency fault current. Secondly, the Bayesian network is established to obtain the fault probability of the faulty component based on the protection action inf0ormation generated by the faulty component, and then the sparse fault characteristics and fault probability of the fault current are normalized to obtain the fault degree of the electrical quantity and switching quantity. Finally, the traditional Dempster Shafer (DS) evidence theory fusion algorithm is improved to solve the problem of conflict of uncertain subsets by weight allocation method, and then the fault degree of electrical quantity and switching quantity is fused by combining Bayesian estimation method and weighting method, so as to achieve accurate fault location. simulation experiments conducted using MATLAB software demonstrate that the proposed method can effectively reduce the evidence conflict at the fault point, and the fault location accuracy is improved by 2% to 4% compared with the traditional DS evidence theory, which has a good engineering application prospect for the fault location of DC distribution network. © 2023, The Authors. All rights reserved.

关键词： Bayesian networks

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Short-Term Interval Prediction of Photovoltaic power Considering Correlation Information Matching of Meteorological Resources and Trend Mutation Perception

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SSRN 2023年

作者： Yang, Mao Li, Yi Zhang, Wei Su, Xin Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China

Since errors in deterministic forecasting of photovoltaic power cannot be avoided, interval prediction can adequately characterize the uncertainty in photovoltaic power, which in turn provides further guidance for decision making in the dispatch department. The current interval prediction method is still incomplete in mining the physical change process of photovoltaic power, and there is a problem of low matching degree of gridded meteorological forecast data in the provincial area. Aiming at the above problems, a short-term interval prediction framework of photovoltaic power considering meteorological correlation information matching and trend mutation perception is proposed in this paper. Firstly, the NWP information is reconstructed for low matching degree power stations, and the weather type is predicted by photovoltaic output level. Next, the prediction interval is calculated based on the state transition probability matrices for trend-change factor, time-correlation factor, and numerical-mutation factor. Finally, the framework of this paper is applied to a photovoltaic power plant in Jilin Province, China, and the results of the arithmetic example show that, compared with other methods, the average RMSE of this paper's method is reduced by 5.3%, and the CWC is improved by at least 2.1%, which verifies the effectiveness of this paper's method. © 2023, The Authors. All rights reserved.

关键词： Decision making

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Wind power Ultra-Short-Term Prediction Method Based on Nwp Wind Speed Correction and Double Clustering Division of Transitional Weather Process

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SSRN 2023年

作者： Yang, Mao Guo, Yunfeng Huang, Yutong Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education [Northeast Electric Power University Jilin132012 China

Wind power prediction technology is important for building novel power systems with a high proportion of renewable energy. Numerical weather prediction (NWP) data quality has a significant impact on the accuracy of ultra-short-term wind power prediction (USTWPP). However, existing NWP do not reflect the adaptability of different weather processes, because of it’ s forecasting errors. In view of this, this paper proposes an USTWPP method based on NWP wind speed correction and transitional weather process division. The BILSTM-INFO-HKELM was first used to correct the NWP wind speed, and then the multiple clustering method was used to divide the transitional weather processes to establish a model for USTWPP based on different scenarios, the overall method was finally applied to a wind farm in west inner Mongolia, China. Compared to the pre-correction, the wind speed forecasted RMSE was reduced by 1.702 and the MAE by 1.366. Based on the wind power ultra-short-term prediction method proposed in this paper, the average reduction in RMSR is 4.96% and in MAE is 4.36% compared to the various comparison methods in this paper. The wind power ultra-short-term prediction method combining wind speed correction and double clustering division of weather scenarios can significantly improve prediction accuracy. © 2023, The Authors. All rights reserved.

关键词： Wind power

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A Review of Coupling and Interaction Studies of Grid-Forming Converters Based on Transient Stability

A Review of Coupling and Interaction Studies of Grid-Forming...

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energy, Electrical and power Engineering (CEEPE), International Conference on

作者： Zhen Tang Shuo Wang Yang Cui Xueting Cheng Yuting Zhao State Grid Shanxi Electric Power Research Institute Taiyuan China Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Northeast Electric Power University Jilin China

ISBN: (数字)9798350375794

ISBN: (纸本)9798350375800

Grid-forming (GFM) inverters, with their synchronous voltage source characteristics, have attracted widespread attention in recent years due to their ability to effectively enhance the stability of power-electronic-based new power systems. The document starts by examining the mechanism of system stability established by GFM and analyzes the issues that need to be addressed urgently after GFM is integrated into the system. Grid-forming control establishes multiple coupling channels with the grid connection point to provide voltage and frequency support. However, the frequency coupling also brings about many interaction issues. The document divides the coupling interaction issues into "internal coupling" and "external interaction" issues based on whether the control structure modification is considered, and evaluates the research path for them.

关键词： Couplings Reviews Resonant frequency power system stability Stability analysis Resonance Transient analysis

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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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Multi-Type Electric Vehicle Schedulability Modeling Method based on User Charging Behavior Characteristics 11

Multi-Type Electric Vehicle Schedulability Modeling Method b...

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11th China International Conference on Electricity Distribution, CICED 2024

作者： Xue, Yinjuan Chen, Qifang Cai, Haiqing Xia, Mingchao Gu, Haohan School of Electrical Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&d Centre Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9798350368345

With the rapid proliferation of Electric Vehicles (EV s), effectively leveraging the regulation potential of EV charging loads has become a prominent issue. This paper proposes a multi-type EV schedulability modeling method based on the analysis of charging behavior characteristics of different user types. The model comprehensively considers the charging characteristics of various types of EV s, including private cars, ride-hailing vehicles, and taxis, utilizing a charging start-stop probability distribution model. Case studies demonstrate that this model can not only accurately reflect the charging demands of EV s but also provide valuable references for strategies involving EV fleet participation in grid regulation. © 2024 IEEE.

关键词： Charging stations

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The HEFT Algorithm Based on Node Merging 8

The HEFT Algorithm Based on Node Merging

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8th International Workshop on control Engineering and Advanced Algorithms, IWCEAA 2024

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

ISBN: (纸本)9798331528881

The task scheduling problem in power systems is complex, especially when communication costs exceed computation costs. This paper proposes an improved HEFT algorithm with a node merging mechanism, merging nodes through hierarchical traversal to assign high-communication-cost tasks to the same processor, reducing communication overhead. Experiments with 499-dimensional and 1614-dimensional matrices from the power system show that the improved algorithm reduces completion time by 5ms and 2ms, respectively, compared to standard HEFT. © 2024 IEEE.

关键词： Scheduling algorithms

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Design and Implementation of a Cross-Platform Real-Time power system simulation Software for the New power system 4

Design and Implementation of a Cross-Platform Real-Time Powe...

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4th International Conference on Intelligent power and systems, ICIPS 2024

作者： Huang, Ying Lu, Yuanhong Zhang, Jingyue Zhan, Jie Zhao, Yanjun Hu, Yufeng China Southern Power Grid State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou Guangzhou510663 China China Southern Power Grid CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou Guangzhou510663 China China Southern Power Grid Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou Guangzhou510663 China China Southern Power Grid National Energy Power Grid Technology R & D Centre Guangzhou Guangzhou510663 China China Southern Power Grid Guangzhou CSG Key Laboratory for Power System Simulation Electric Power Research Institute Guangzhou510663 China

ISBN: (纸本)9798331532765

With the rapid increase in renewable energy installation nodes and the substantial enhancement of switching frequencies in the new power system, this paper proposes a design scheme for a cloud simulation software that employs the Latency Insertion Method (LIM) to decompose large-scale new power system models into several subsystems, enabling multi-platform integrated parallel computing. The self-developed platform meets the demands of ultra-large simulation scales, ultra-small simulation time steps, and massive simulation computations in power systems. Experimental results demonstrate that the accelerated simulation technology, which integrates model segmentation using LIM with multi-core parallel execution, can enhance the simulation speed by up to 858 times while maintaining simulation accuracy. This significantly improves simulation efficiency and is suitable for large-scale simulations of new power systems. © 2024 IEEE.

关键词： power systems computer aided design

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Clustering and Equivalent Modeling Method for Direct-Drive Wind Farms Based on Particle Swarm Neural Network 4

Clustering and Equivalent Modeling Method for Direct-Drive W...

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4th International Conference on energy, power and Electrical Engineering, EPEE 2024

作者： Tu, Liang Huang, Libin Guo, Haiping Hu, Binjiang Zhang, Jingyue Luo, Hui State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&d Centre China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System China Southern Power Grid Guangzhou China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&d Centre Guangzhou China

ISBN: (纸本)9798331518066

In the realm of large-scale integration of wind farms or clusters into power grids, the fault transient characteristics of these grids have experienced significant transformations. Unfortunately, the prevalent single-machine equivalent models are inadequate in accurately depicting the fault transient behavior of wind farms or clusters. Moreover, their simulation computations are exceedingly intensive, resulting in suboptimal simulation efficiency. To address these challenges, this paper introduces a clustering and equivalent modeling approach tailored for direct-drive wind farms, leveraging the capabilities of a particle swarm neural network. Initially, a transient model for direct-drive wind turbines is formulated, and fault characteristic influence factors are established through theoretical analysis. These factors encompass the distance between the wind turbine and the point of common coupling (PCC), the implementation of DC-side current limiting measures, wind speed, and reactive power at the outlet. Following this, the Euclidean distance of the influence factor set is computed, and the initial cluster centers of wind turbines are derived using an enhanced max-min distance method. Ultimately, an equivalent clustering model is formulated by utilizing the influence factors and initial cluster centers as the training set. simulation outcomes reveal that, in comparison to the single-machine equivalent model, this method enhances simulation efficiency by a range of 62% to 67% and reduces the steady-state error in fault current simulation by 0.8% to 1.9%. © 2024 IEEE.

关键词： Windmill

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control and Stability of Large-scale power system with Highly Distributed renewable energy Generation:Viewpoints from Six Aspects

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CSEE Journal of power and energy systems 2023年第1期9卷 8-14页

作者： Qing-Hua Wu Anjan Bose Chanan Singh Joe H.Chow Gang Mu Yuanzhang Sun Zhaoxi Liu Zhigang Li Yang Liu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China School of Electrical Engineering&Computer Science Washington State UniversityPullmanWA 99164USA Department of Electrical and Computer Engineering Texas A&M UniversityCollege StationTX 77843USA Department of Electrical Computer and Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNYUSA Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

power systems are moving toward a low-carbon or carbon-neutral future where high penetration of renewables is *** conventional fossil-fueled synchronous generators in the transmission network being replaced by renewable energy generation which is highly distributed across the entire grid,new challenges are emerging to the control and stability of large-scale power *** analysis and control methods are needed for power systems to cope with the ongoing *** the CSEE JPES forum,six leading experts were invited to deliver keynote speeches,and the participating researchers and professionals had extensive exchanges and discussions on the control and stability of power ***,potential changes and challenges of power systems with high penetration of renewable energy generation were introduced and explained,and advanced control methods were proposed and analyzed for the transient stability enhancement of power grids.

关键词： Distributed energy resources high converter penetration power system control renewable energy generation stability control transient stability

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