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7th Asia Conference on Power and Electrical Engineering, ACPEE 2022

作者： Gongye, Lingjiao Zhang, Dahai Li, Wei Wang, Xueqin Wu, Chuanjian Beijing Jiaotong University School of Electrical Engineering Beijing China Skl of Sgpc Nari Group Corporation State Key Laboratory of Smart Grid Protection and Control Nanjing China

ISBN: (纸本)9781665418195

The removal of the DC line may lead to power flow transfer, which leads to the wrong operation of the AC line distance III protection. To solve this problem, a modified distance backup protection that integrates DC control information is proposed. First, analyze the characteristics of DC side control information and propose a power flow transfer identification scheme that integrates DC control information. Subsequently, the modified distance backup protection is constructed using the identification results of the power flow transfer. Finally, an AC/DC hybrid model was established to verify the feasibility and fault resistance capability of the proposed scheme. © 2022 IEEE.

关键词： Electric load flow

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Analysis of influence of virtual inertia of grid-forming converter on transient stability characteristics 5

Analysis of influence of virtual inertia of grid-forming con...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Huang, Xifang Zhu, Ling Li, Wei Li, Mingfei Quan, Xiangiun Wu, Zaijun Research Institute NARI/SGEPRI State Key Laboratory of Smart Grid Protection and Control Nari Group Corporation/State Grid Electric Power Nanjing China Southeast University Seu School of Electrical Engineering Nanjing China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

Due to its different characteristics from traditional synchronous generator, grid-forming converter (GFM-converter) affects the transient characteristics of the system when it is linked to the power grid. The mathematical model of the GFM-converter is built to describe its dynamic characteristics. Then, the transient process of the GFM-converter is analyzed qualitatively with the power-angle curve. The phase diagram method is used to study quantitatively and verify the validity of the above qualitative analysis. Finally, the influence of virtual inertia JGFM on the transient response is analyzed. In the case that equilibrium point exists after fault, decreasing virtual inertia improves the transient stability of the GFM-converter by increasing the damping ratio. When the equilibrium point does not exist after fault, the increase of JGFM reduces the virtual power angle at the time of fault clearing, and the power imbalance degree of the GFM-converter is reduced, thus its transient stability performance is improved. © 2022 IEEE.

关键词： Phase diagrams

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Assessment of Static Voltage Stability Margin for Power Systems with Causal Decomposition and Reverse Feature-Enhanced Temporal Convolutional Networks

Assessment of Static Voltage Stability Margin for Power Syst...

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IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Haifeng Zhou Xianyu Zha Qi Pan Naishuang Li Jiabin Zhang Jiacheng Liu State Key Laboratory of Smart Grid Protection and Operation Control NARI Group Corporation (China Electric Power Research Institute) Nanjing China

ISBN: (数字)9798350386127

ISBN: (纸本)9798350386134

Rapid and accurate static voltage stability assessment is crucial for the safe operation of large-scale interconnected power grids. Existing methods have failed to effectively filter key input variables in massive measurement data, limiting assessment accuracy. This study proposes an assessment method based on causal decomposition and reverse feature-enhanced temporal convolution networks. Initially, using bottom-layer measurement data as input, key variables are selected through causal decomposition, reducing the original feature set and enhancing computational efficiency. Subsequently, a reverse feature-enhanced temporal convolution model is constructed to fully mine data characteristics and achieve high precision assessment. Validation in an improved four-machine two-area simulation system demonstrates that this method significantly enhances estimation accuracy and algorithm performance while reducing the dimensionality of original variables.

关键词： Adaptation models Accuracy Correlation Convolution Power system stability Predictive models Feature extraction Stability analysis Data models Convolutional neural networks

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Ground Circulating Current Suppression of Flexible Interconnection System of Distribution Station Area based on Three-Phase Four-Leg Converter

Ground Circulating Current Suppression of Flexible Interconn...

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Power Energy Systems and Applications (ICoPESA), International Conference on

作者： Xiaoming Zeng Zhigang Wang State Key Laboratory of Smart Grid Protection and Control NARI Group Corporation (State Grid Electric Power Reasearch Insitute) Nanjing China

Flexible interconnection of low-voltage distribution station area with power electronic device can realize dynamic capacity increase and coordination. When three-phase four-leg converter is used as a flexible interconnection device, there is no need to the isolation transformer, which can reduce the volume and cost of the system, but it will generate circulating current on the ground line. According to the main circuit topology of the system, the average circuit model of ground circulating current is established, and the influencing factors of ground circulating current are deduced. The low-frequency circulating current suppression strategy based on the average duty cycle control of the fourth leg and the high-frequency circulating current suppression method based on the DC side common mode inductor are proposed respectively for the low frequency and high frequency components of the ground circulating current. Finally, the simulation results show the effectiveness of the proposed average circuit model and the suppression method.

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A Novel Method for Directly Calculating Dynamic Equivalent Generator Parameters

A Novel Method for Directly Calculating Dynamic Equivalent G...

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IEEE Asia Power and Energy Engineering Conference (APEEC)

作者： Yuqiang Hou Wei Zhao Wei Li Ling Zhu NARI Group Corporation (State Grid Electric Power Research Institute) State Key Laboratory of Smart Grid Protection and Control Nanjing China

The dynamic equivalent of large power grid needs to calculate the dynamic aggregation of equivalent generator parameters for a given synchronous units group. In this paper, the weighted aggregation method commonly used in engineering is reviewed, and the deficiency of capacity weighting method is pointed out, then a direct parameters calculation method for dynamic equivalent generator based on EEAC and the unit-grid phasor diagram is proposed. Its key techniques are to using the complementary-cluster center-of-inertia relative motion transformation (CCCOI-RM) provided by the EEAC method, the initial value of the power angle for corresponding equivalent generator of the coherent generators group at the fault moment is calculated, and the impedance parameters of the equivalent generator are solved step by step by different forms of unit-grid phasor equations according to the feature that the power angle cannot be changed abruptly before and after the fault moment. Compared with the weighted aggregation calculation method, the proposed method is simpler and has a clearer physical concept. Simulation results based on the real power grids verify the effectiveness of the proposed method.

关键词： Simulation Power system dynamics Voltage Wind power generation Generators Mathematical models Synchronous generators

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Design of Experiment Management System for Stability control System Based on Blockchain Technology 1st

Design of Experiment Management System for Stability Control...

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1st BenchCouncil International Federated Intelligent Computing and Block Chain Conferences, FICC 2020

作者： Cui, Xiaodan Lei, Ming Yang, Tianshu Wu, Jialong Feng, Jiaqi Yang, Xinlei Nanjing211106 China State Key Laboratory of Smart Grid Protection and Control Nanjing211106 China

ISBN: (纸本)9789811611599

Stability control system (SCS) plays a very important role in the operation of power systems, so it is correspondingly essential to ensure the reliability of the SCS during its experimental and verification process. However, there are numerous problems in the management of the paper form based experiment mode of SCS today, such as long circulation cycle caused by low work efficiency, insecure and diseconomy on storage. More importantly, it is difficult to query and review historical records quickly, and it may even lead to the loss of records for various reasons. In this paper, taking advantage of blockchain technology, all the information of each experimental stage of SCS, including the approval information, experimental environment information, experimental equipment information of each manufacturer, experimental test reports and conclusions, are packaged and distributed managed. And then, a blockchain based experimental management system framework with the unified data form and module interface is proposed, in which the whole process of process record can be traced and cannot be tampered with. The experimental management system can be applied in the whole process of the SCS, including the experiment scheme making, experiment environment constructing, experiment processing, result evaluating, and results storage, etc. The blockchain based mechanism and system framework is expect to take many advantage to experiment management of SCS. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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Analysis on the Influence of the DC bias on spatial magnetic flux leakage in the transformer

Analysis on the Influence of the DC bias on spatial magnetic...

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2022 IEEE International Conference on High Voltage Engineering and Applications, ICHVE 2022

作者： Zheng, Yuping Pan, Shuyan Xia, Yu Ouyang, Xi Shang, Hujun Zhou, Quan Nari Group Corporation Nanjing211106 China State Key Laboratory of Smart Grid Protection and Control Nanjing211106 China School of Electrical Engineering Chongqing University Chongqing China

ISBN: (数字)9781665407502

ISBN: (纸本)9781665407502

Magnetic flux leakage, as a basic physical parameter in power transformer, can be utilized to characterize the status of the winding. And the DC biasing, as a common abnormal operation condition, is caused by solar storms, DC power transmission and some railway power transmission. It can induce the current bias and the core saturation, further changing the distribution of the magnetic flux leakage. Therefore, it is significant and valuable to analyze the effect of DC biasing on spatial magnetic leakage flux. In the paper, we design a transformer finite element model with its physical fieldcircuit simulation module. The model with some detailed winding structure can obtain the accurate magnetic field signal. Then the effect of different degrees DC biasing on the magnetic leakage flux is analyzed in the inner key positions. And the 10kV shrunken experimental transformer imitating the 110 k V transformer is selected as the research object. Depending on the experimental platform, we obtain the actual magnetic field signals and explore the incidence relation between the magnetic leakage flux and the DC biasing. © 2022 IEEE.

关键词： Power transmission

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Source-Load Joint Probability Prediction Based on Transformer Model 5

Source-Load Joint Probability Prediction Based on Transforme...

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5th IEEE International Conference on Artificial Intelligence and Big Data, ICAIBD 2022

作者： Hu, Pingzhao Shan, Xin Hu, Diangang Fu, Jiayu Wang, Chen Zhang, Kaifeng Southeast University Key Laboratory of Measurement and Control of Cse Ministry of Education Nanjing China Co. Ltd. State Grid Nari Technology Co. Ltd. State Key Laboratory of Smart Grid Protection and Operation Control Nanjing China State Grid Gansu Electric Power Co. Ltd. Gansu China

ISBN: (纸本)9781665499132

Renewable energy power generation prediction, including wind and photovoltaic power prediction, is usually performed separately from load prediction, while there are significant internal relationships between renewable energy power generation and load consumption. Therefore, exploring the relationship between source and load, and implementing sourceload joint prediction may improve the accuracy of source-load prediction simultaneously. This paper proposes a source-load joint probability prediction method, PCMDT (Probability-CNN-Multi-Decoder-Transformer), based on Transformer model. Firstly, we analyzed the possible aspects of the relationship between renewable energy and load. Then the CMDT(CNN-Multi-Decoder-Transformer) model was used to realize the point prediction of renewable energy power generation and load power. Next, the conditional quantile was obtained by optimizing the quantile loss function (Pinball Loss) to realize the joint probability prediction of source and load. Finally, the model was tested on a public state-level dataset. Comparing the results of source-load joint prediction with non-joint prediction, the proposed model can improve the accuracy of renewable energy and load prediction. © 2022 IEEE.

关键词： Forecasting

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Transmission Line Distance protection Under Current Transformer Saturation

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Journal of Modern Power Systems and Clean Energy 2021年第1期9卷 68-76页

作者： Yuping Zheng Tonghua Wu Feng Hong Gang Yao Jimin Chai Zhinong Wei the College of Energy and Electrical Engineering Hohai UniversityNanjing 210098China State Key Laboratory of Smart Grid Protection and Control NARI Group CorporationNanjing 211106China Changzhou Institute of Technology Changzhou 213032China

Conventional transmission line distance protection approaches are subject to malfunction under reverse fault-induced current transformer(CT) saturation for the typically employed breaker-and-a-half configuration. This paper addresses this issue by proposing a new distance protection approach that combines the blocking and unblocking criteria of distance protection based on the values of incomplete differential current,operation voltage, and current harmonic content. The proposed approach is verified by theoretical analysis, dynamic simulation testing, and field operation to ensure that the obtained distance protection is reliable and refrains from operating unnecessarily under reverse fault-induced CT saturation in the breaker-and-ahalf configuration. Meanwhile, the proposed approach is demonstrated can operate reliably when forward faults occur or various reverse faults are converted to forward faults.

关键词： Breaker-and-a-half configuration current transformer(CT)saturation distance protection power frequency variation operation voltage

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A Practical Method for Generating Day-Ahead Output Probabilistic Scenarios of Multiple Wind Farms Based on K-Shape Clustering

A Practical Method for Generating Day-Ahead Output Probabili...

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IEEE International Conference on Power and Energy Systems (ICPES)

作者： Lin Bo Taishan Xu Mengfu Tu Jinjun Lu NARI Group Co. Ltd.(State Key Laboratory of Smart Grid Protection and Control) Nanjing Chinas

The volatility and uncertainty of wind power bring severe challenges to the power system, and the modeling of multi-wind farm output scenarios considering the uncertainty of wind power is of great significance in power system dispatching decision-making. Especially for area/ province with abundant wind power resources, where the reliability of the dispatching plan can be strongly affected by the volatility of large amount of wind power. In this paper, a practical method of generating probabilistic scenarios for day-ahead wind power output is proposed for provincial power grid with high proportion of wind power. Firstly, the K-Shape clustering algorithm is used to cluster the wind farm stations, and then the output scenario are generated by using the total wind power forecast value and forecast error probability distribution characteristics of each aggregated station. After arrangement and combination of the aggregated stations’ scenes, the scenario minimization based on probability distance was conducted for clustering reduction to obtain the typical output scenes, and then the typical output scenes were assigned to each station according to the forecast value of the station to obtain the probability output scenes of each station. It is verified by actual power grid data that the scenarios generated by this method can combine with wind power predictions to well depict the random fluctuation of multi-wind farms output and has a good application prospect in the practice of day-ahead dispatching decision making.

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