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SSRN 2024年

作者： Sun, Zhenglong Long, Hao Li, Zewei Gao, Bo Wei, Xiaoqiang Belikov, Juri Levron, Yoash Department of Electrical Engineering Key Laboratory of Modern Power System Simulation and Control & Renewable Energy State Grid Jiashan County Power Supply Company Jiaxing China State Grid Heilongjiang Electric Power Company Limited Heilongjiang China The Andrew and Erna Viterbi Faculty of Electrical Engineering Technion Israel Institute of Technology Haifa Israel Department of Software Science Tallinn University of Technology Tallinn Estonia Northeast Electric Power University China

The increasing interconnectivity of power systems and the integration of renewable energy sources into the grid have exacerbated the low-frequency oscillation problem, which directly impacts the stability of the power grid. The performance of wide-area damping control (WADC), which is an effective oscillation suppression technique , is susceptible to false data injection attacks (FDIA). This study proposes a non-intrusive data verification method using an adaptive variational autoencoder (AVAE) combined with a deep convolutional neural network (DCNN) to enhance WADC’s resistance to FDIA. The method integrates data dimensionality reduction of AVAE and reconstruction capabilities with DCNN’s feature extraction advantages. Itemploys adaptive thresholds to dynamically track grid data fluctuations, accurately distinguishing between normal and abnormal measurements and improving attack detection and performance discrimination. In addition, the study proposes an intelligent repair process based on latent representations for anomalous data in the repair module, using hierarchical clustering and Gaussian mixture models post-Bayesian inference to repair data. AVAE then reconstructs the repaired data, mitigating attack impacts. simulations on IEEE 39-Bus, 68-Bus, and 118-bus systems demonstrate that this method effectively detects network attacks and restores manipulated signals with minimal reconstruction errors, thus ensuring grid stability and reliability. © 2024, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Research on the Grid-connected Photovoltaic power Scheduling Strategy Considering the Flexible Load

Research on the Grid-connected Photovoltaic Power Scheduling...

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energy Engineering and power systems (EEPS), International Conference on

作者： Tao Meng Chenggang Li Dexin Li Jiajun Zhang Electric Power Research Institute State Grid Jilin Electric Power Co. Ltd Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education School of Electrical Engineering Northeast Electric Power University Changchun China Electric Power Research Institute State Grid Jilin Electric Power Co. Ltd Changchun China

With the target of "peak carbon dioxide emission" and "carbon neutrality", the installed capacity of renewable energy power generation is increasing rapidly. To improve the absorption capacity of renewable energy, the frequency regulation ability of flexible load is considered. Diffusion strategy is an optimal strategy for the distributed multi-agent system. Considering the flexible load, the grid-connected photovoltaic power applies the diffusion strategy to optimize the scheduling strategy. The effectiveness of the proposed optimal algorithm is verified by a simulation example. The results show that the proposed algorithm can realize frequency regulation, and improve the installed capacity of photovoltaic power generation.

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

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

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Intelligent power and systems (ICIPS), International Conference on

作者： Ying Huang Yuanhong Lu Jingyue Zhang Jie Zhan Yanjun Zhao Yufeng Hu State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou 510663 China Southern Power Grid Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou 510663 China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou 510663 China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou 510663 China Southern Power Grid Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou Guangzhou China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

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.

关键词： renewable energy sources Accuracy Computational modeling Switching frequency Software algorithms Random access memory Parallel processing Software Real-time systems power systems

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

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

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

作者： Liang Tu Libin Huang Haiping Guo Binjiang Hu Jingyue Zhang Hui Luo China Southern Power Grid State Key Laboratory of HVDC Electric Power Research Institute 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 China Southern Power Grid CSG Key Laboratory for Power System Simulation Electric Power Research Institute Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou China

ISBN: (数字)9798331518066

ISBN: (纸本)9798331518073

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 ${6 2 \%}$ to ${6 7 \%}$ and reduces the steady-state error in fault current simulation by ${0 . 8 \%}$ to ${1 . 9 \%}$.

关键词： Training Computational modeling Wind speed Current measurement Wind farms Data models Wind turbines Steady-state Transient analysis Particle swarm optimization

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Analysis of the influence of wind farms in full operating conditions on the torsional vibration of the shaft system of synchronous generators

Analysis of the influence of wind farms in full operating co...

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2021 International Conference on power system technology, powerCON 2021

作者： Jia, Qi Zhai, Wenchao Zhang, Qiang Sun, Feng Shen, Mohan Research Institute State Grid Liaoning Electric Power Shenyang China Northeast Electric Power University Min. of Educ. Key Laboratory of Modern Power System Simulation Control and Green Power Technology Jilin China

ISBN: (纸本)9781665407373

The power oscillation induced by the large-scale integration of wind power into the power grid has become one of the important issues affecting the safe and stable operation of the power grid. Aiming at the dynamic interaction between wind farms and synchronous generators, based on the additional excitation signal injection method, the influence of DFIG and PMSG wind farms on the damping characteristics of each torsional vibration mode of synchronous generators under full operating conditions is analyzed. By applying an AC voltage signal at both ends of the field winding to stimulate rotational speed oscillation, observe the difference in the free response characteristics of rotational speed disturbances, identify the electromechanical coupling characteristics between the wind farm and the synchronous generator set, and reveal the influence of the wind farm type and operating conditions on the shaft system of the synchronous generator set. The mechanism of torsional vibration. Finally, the validity of the theoretical analysis is verified based on time-domain simulation. © 2021 IEEE.

关键词： Synchronous generators

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Refined power modeling method of ultra-short-term wind power cluster based on power reverse deduction

Refined power modeling method of ultra-short-term wind power...

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IEEE Conference on energy Internet and energy system Integration (EI2)

作者： Yupeng Sun Mao Yang Chenglian Ma Yunpeng Jia Guozhong Fang Key Laboratory of Modern Power System Simulation and Control & Renewable EnergyTechnology Ministry of Education Northeast Electric Power University Jilin China Northeast Electric Power University Jilin China Jilin Power Supply Company of State Grid Jilin Electric Power Co. Ltd. Jilin China State Grid Northeast China Branch Shenyang China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

The accurate prediction of wind power provides a guarantee for the safety and stability of the power system and the power market trading. The existing wind power prediction methods mainly focus on the depth of the model, and improve the accuracy of the prediction by constantly improving the model and deepening the model, but they ignore the limitations of the model itself. In this paper, a fine modeling method for wind power is proposed, and the prediction accuracy is improved by horizontal expansion of the model. Firstly, the power output class and its NWP characteristics are determined by power reverse deduction, and the power output class is divided by the degraded and simplified U-net model. Then, Non-stationary Transformer (NSTransformer) is introduced to model each output level separately to get the predicted power. Finally, the proposed method is applied to a wind farm cluster in China. The accuracy of the proposed method is higher than other methods in ultra-short-term prediction, which proves the reliability and effectiveness of the proposed method.

关键词： Accuracy system integration Predictive models Wind power generation power system stability Wind farms Transformers Stability analysis Safety Thermal stability

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Research on Multi-Objective Planning of Electric Vehicle Charging Stations Considering the Condition of Urban Traffic Network

arXiv

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arXiv 2022年

作者： Wang, Limeng Yang, Chao Zhang, Yi Bu, Fanjin Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Grid Harbin Power Supply Company Substation Secondary Maintenance Center Harbin150036 China

As an important supporting facility for electric vehicles, the reasonable planning and layout of charging stations are of great significance to the development of electric vehicles. However, the planning and layout of charging stations is affected by various complex factors such as policy economy, charging demand, user charging comfort, and road traffic conditions. How to weigh various factors to construct a reasonable model of charging station location and capacity has become a major difficulty in the field of electric vehicle charging facility planning. Firstly, this paper constructs the location and capacity optimization model of the charging station with the goal of maximizing the revenue of operators and minimizing the user's charging additional cost. At the same time, the road time-consuming index is introduced to quantify the impact of road congestion on the user's charging additional cost, so as to effectively improve the user's satisfaction during charging. Then, aiming at the charging station planning model, a non-dominated sorting genetic algorithm with an elite strategy (NSGA-Ⅱ) based on chaos initialization and arithmetic crossover operator is proposed. Finally, taking the Haidian District of Beijing as the simulation object, the results show that compared with the situation of urban traffic networks not considered, the model proposed in this paper significantly reduces the cost of lost time of users by 11.4% and the total additional cost of users' charging by 7.6%. It not only ensures the economy of the system, but also effectively improves the charging satisfaction of users, which further verifies the feasibility and effectiveness of the model, and can provide a reference for the planning and layout of charging stations in the future. © 2022, CC BY-NC-ND.

关键词： Location

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simulation Testing of Large-Scale Grid-Connected Wind power with energy Storage system Based on Active Support Performance Evaluation Indices

Simulation Testing of Large-Scale Grid-Connected Wind Power ...

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Electrical Engineering and Automation (IFEEA), International Forum on

作者： Yihua Zhu Yun Hu Liang Tu Mingzhang Su Chao Luo State Key Laboratory of HVDC Electric Power Research Institute CSG 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

This paper establishes simulation modeling for large-scale grid connected wind power with energy storage system (ESS). The conventional grid-following (GFL) based ESS is used as a reference object to test the active support performance of large-scale grid-connected wind power with grid-forming (GFM) based ESS with active support performance evaluation indices in different scenarios. (1) Small disturbance evaluation indices: The point of common coupling (PCC) frequency/voltage drop depth and recovery time. (2) Large disturbance evaluation indices: The PCC frequency/voltage drop depth and rise height after fault removal. The output active/reactive power drop depth and rise height/recovery time after fault removal. (3) Island capability evaluation indices: The PCC frequency/voltage fluctuation amplitude at the moment of switching and system stability after switching.

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The HEFT Algorithm Based on Node Merging

The HEFT Algorithm Based on Node Merging

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control Engineering and Advanced Algorithms (IWCEAA), International Workshop on

作者： Ying Huang Yuanhong Lu Jie Zhang Jingyue Zhang Haiping Guo National Energy Power Grid Technology R&D Centre Guangzhou 510663 State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou 510663 Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou 510663 Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou 510663 Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou 510663 CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou 510663 Guangzhou China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

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.

关键词： Costs control engineering Processor scheduling Conferences Merging power systems Standards

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Coordinated Optimal Configuration Method of Wind power Load Shedding Rate and energy Storage Aiming at Active Frequency Support

Coordinated Optimal Configuration Method of Wind Power Load ...

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China International Electrical and energy Conference (CIEEC)

作者： Xiuyu Yang Jian Peng Yuxuan Liu Gang Miu Guochao Zhang Zhengyin Zhu Key Laboratory of Modern Power System Simulation Control and New Green Energy Technology of Ministry of Education Northeast Electric Power University Jilin China State Grid Xinjiang Power Supply Company State Grid Urumqi Power Supply Company Urumqi City China State Grid Jilin Power Supply Company State Grid Jilin Power Supply Company Jilin China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

With the increase of renewable energy, the system frequency modulation ability is insufficient, and the relevant departments require that renewable energy should have the active support ability of power system frequency change. Long-term active load shedding to achieve frequency support will cause power generation loss and economic damage; if the maximum output of the wind turbine is taken as the active support task by the energy storage, the amount of energy storage required is large. Therefore, this paper proposes a coordinated optimal allocation method of wind power load shedding rate and energy storage capacity with the goal of frequency active support. From the economic point of view, the optimal allocation relationship between wind power load shedding rate and energy storage capacity allocation is analyzed to find the optimal setting of load shedding rate and energy storage capacity.

关键词： renewable energy sources Frequency modulation Costs Wind energy Load shedding Wind power generation Wind turbines

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