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2022 power System and Green Energy Conference, PSGEC 2022

作者： Ren, Xiancheng Xu, Taishan Zhang, Yin Bao, Yanhong Wu, Feng Zhang, Jinlong State Key Laboratory of Smart Grid Protection and Control Nari Technology Co. Ltd. Nanjing China

ISBN: (数字)9781665499934

ISBN: (纸本)9781665499934

Aiming at the problem that it is difficult to achieve the quantitative evaluation of transient power angle stability based on artificial intelligence, a quantitative intelligent evaluation method of transient power angle stability based on cluster grouping is proposed. Firstly, the key features of transient power angle stability are selected by the method of comprehensive physical mechanism and data mining. According to the difference requirement parameters of the key features of the train samples, the similar samples are minimized and clustered into groups. The center sample of each group is determined based on the comprehensive minimum of the stable mode difference index. Based on each group of center samples, a transient power angle stability margin estimation model is established and parameters are optimized by linear programming. Determine the effective group to which the new mode belongs by the effective mode distance of each group of samples. Use the model corresponding to each effective group to estimate the margin of the new mode, and take the minimum value of the estimated margin of all effective groups as the estimated value of the transient stability margin of the new mode to realize quantitative intelligent evaluation of transient power angle stability. The effectiveness of the proposed method is verified by an example of power grid. © 2022 IEEE.

关键词： Transients

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Deep neural network based acoustic pattern recognition system for fault localization application

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Applied Mathematics and Nonlinear Sciences 2024年第1期9卷

作者： Cui, Yao Huang, Xin Zhang, Xin Nari Group Corporation State Grid Electric Power Research Institute Jiangsu Nanjing211106 China State Key Laboratory of Smart Grid Protection and Control Jiangsu Nanjing211106 China

This paper explores the process of traditional voiceprint recognition, analyzes the traditional GMM recognition algorithm, and proposes a GE2E-based voiceprint recognition algorithm by combining it with the deep neural network. It firstly uses the Bi-GRU network to replace the LSTM network to prevent the lack of semantic information, then adds the SGD algorithm to optimize the speech features, and finally improves the stability and accuracy of recognition by the GE2E loss function. On this basis, a voiceprint recognition system based on GE2E is designed, and the overall performance of the system is tested. Additionally, a voiceprint recognition system is being explored for fault localization. The results show that the recognition accuracy of male voiceprints in the test is at [0.89,0.95], and the recognition accuracy of female voiceprints is at [0.88,0.96], and there is not much difference in the voiceprint recognition accuracy of the voiceprint recognition system for both male and female students, and the overall recognition accuracy is greater than 0.9. When applied in fault location, the error between the measured distance and the actual fault distance is within 0.1 meters, enabling fault location. © 2023 Yao Cui, Xin Huang and Xin Zhang, published by Sciendo.

关键词： Deep neural networks

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Quantitative analysis for coupling between frequency dynamic and power angle oscillation 4

Quantitative analysis for coupling between frequency dynamic...

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4th IEEE International Conference on power, Intelligent Computing and Systems, ICPICS 2022

作者： Liu, Fusuo Wang, Chao Ma, Ruicong Li, Wei Cao, Yongji Chang, Haijun Zhang, Hengxu Gao, Zhimin State Key Laboratory of Smart Grid Protection and Control NARI Group Corporation State Grid Electric Power Research Institute Nanjing China NARI Group Corporation State Grid Electric Power Research Institute Nanjing China Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong University Jinan China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

With the increasing penetration of power electronic devices, the behaviors of the power system become more and more complex. This paper analyzes the coupling characteristics between the frequency dynamics and power angle oscillation. The mechanism of frequency response and power angle oscillation is derived. The evaluation indexes are proposed to quantify the frequency response, power angle oscillation, and coupling characteristics. The coupling degree of the frequency dynamics and power angle oscillation is depicted by the Pearson correlation coefficient. The impacts of power angle oscillation on the frequency response are attained through time-domain simulation and theoretical analysis. The results show that the proposed evaluation indexes are effective to quantify the coupling characteristics. Additionally, there is positive correlation between the frequency dynamics and power angle oscillation. © 2022 IEEE.

关键词： Frequency response

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Comparison and improvement of key feature selection methods for intelligent assessment of transient power angle stability 5

Comparison and improvement of key feature selection methods ...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Zhang, Yin Xu, Taishan Ren, Xiancheng Bao, Yanhong Wu, Feng Zhang, Jinlong Nari Technology Co. Ltd. State Key Laboratory of Smart Grid Protection and Control Nanjing China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

key feature selection is of great significance for intelligent assessment of transient power angle stability of power system. This paper proposes a key feature selection method for improved Relief. Through analyzing and comparing the applicability of correlation coefficient, mutual information and Relief, three representative key feature selection methods, in the intelligent assessment of transient angle stability of power system, the applicability of Relief is better. The Relief index reflects the strength of the feature to classify transient power angle stability and instability. By eliminating redundancy and increasing the weight of unstable samples, the accuracy of index calculation and the ability to adapt to sample imbalance are improved. Based on improved Relief, feature is selected by iterative optimization, which can automatically screen out the optimal key feature set. The effectiveness of the method is verified by an example of power grid. © 2022 IEEE.

关键词： Transients

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Research on DC protection Strategy in Multi-Terminal Hybrid HVDC System

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Engineering 2021年第8期7卷 1064-1075页

作者： Yuping Zheng Jiawei He Bin Li Tonghua Wua Wei Dai Ye Li State Key Laboratory of Smart Grid Protection and Control State Grid Electric Power Research Institute(NARI Group Corporation)Nanjing 211106China Key Laboratory of Smart Grid of Ministry of Education Tianjin UniversityTianjin 300072China College of Energy and Electrical Engineering Hohai UniversityNanjing 210098China

Multi-terminal hybrid high-voltage direct current(HVDC)systems have been developed quickly in recent years in power transmission ***,for voltage-source converter(VSC)stations in hybrid HVDC systems,no direct current(DC)filters are *** addition,the DC reactor is also not installed at the line end because the DC fault can be limited by the converter *** means that the boundary element at the line end is absent,and the single-ended protections used in line commutated converter(LCC)based HVDC(LCC-HVDC)systems or VSC-HVDC systems cannot distinguish the fault line in multi-terminal hybrid HVDC *** paper proposes a novel singleended DC protection strategy suitable for the multi-terminal hybrid HVDC system,which mainly applies the transient information and active injection concept to detect and distinguish the fault *** with the single-ended protections used in LCC-HVDC and VSC-HVDC systems,the proposed protection strategy is not dependent on the line boundary element and is thus suitable for the multiterminal hybrid HVDC *** corresponding simulation cases based on power systems computer aided design(PSCAD)/electromagnetic transients including DC(EMTDC)are carried out to verify the superiority of the proposed protection.

关键词： Multi-terminal hybrid HVDC system Single-ended protection Transient information Active injection

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A Synchronization Stability Enhancement control Method for 100% Converter-based System Based on An Improved Kuramoto Model 5

A Synchronization Stability Enhancement Control Method for 1...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Zou, Yan Wang, Zhen Li, Zhicheng Xiong, Jiali Deng, Chaoping Cai, Qiang Zhejiang University School of Electrical Engeerning Hangzhou China State Grid Fujian Electric Power Research Institute Fujian Key Laboratory of Protection and Operation Control for Smart Grid Fuzhou China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

In this paper, a synchronization stability enhancement control method is developed to improve the stability performance of power systems with 100% converter-based renewable generation. An improved Kuramoto-type model is established with a time-variable power injection taken into consideration, which can represent load and/or generation variation. Then a consensus tracking controller (CTC) to help all generators to trace a reference bus with specified common frequency rapidly is developed. A group of new synchronization conditions and the attraction region based on the improved Kuramoto-type model are then derived. Further, a control gain design scheme for CTC is proposed based on the two derived stability rules, i.e., the phase angle cohesiveness and the frequency bounded. Finally, a modified three-machine nine-bus system is used to validate the effectiveness of the proposed method and a comparison study result show that the transient stability performance of 100% power-converter system can be greatly improved. © 2022 IEEE.

关键词： Synchronization

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An Integer Variable Reduction and Neighborhood Search Cutting Plane Method for Security Constrained Unit Commitment 4

An Integer Variable Reduction and Neighborhood Search Cuttin...

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4th International Conference on power and Energy Technology, ICPET 2022

作者： Ding, Qia Ye, Jun Wang, Mengchang Zhang, Yantao Lu, Chunling Wang, Wen State Key Laboratory of Smart Grid Protection and Control Nanjing China Alibaba Group Alibaba Damo Academy Hangzhou China

ISBN: (数字)9781665480796

ISBN: (纸本)9781665480796

Security-constrained unit commitment (SCUC) is the foundation to ensure the safe and economic operation of power systems. A large number of integer variables and complex network security constraints are the main barriers that limit the computation efficiency of the SCUC problem. In this paper, the congestion information is used to identify the units that play a key role in alleviating transmission congestion, in the process of iterative solving of the SCUC. Then the commitment statuses of non-critical units are fixed, and the number of integer variables is reduced. Additionally, a neighborhood search cutting plane is designed and added to the model so as to reduce the branch-and-bound search space of the mixed integer programming problem. The simulation results of the 3375-bus case demonstrate that the proposed method can significantly improve the solving efficiency compared with the traditional method. © 2022 IEEE.

关键词： Complex networks

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A Dual-Objective Optimization control Strategy with Markov Forecast for Battery Energy Storage System to Mitigating Wind Farm Fluctuations 6th

A Dual-Objective Optimization Control Strategy with Markov F...

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6th PURPLE MOUNTAIN FORUM on smart grid protection and control, PMF2021

作者： Gu, Haotian Hou, Kai Jiang, Yingwei Yin, Hang Liu, Jing Zhong, Xu NARI Group Corporation/State Grid Electric Power Research Institute Jiangsu Province Nanjing211000 China State Key Laboratory of Smart Grid Protection and Control Jiangsu Province Nanjing211000 China

ISBN: (纸本)9789811671555

In a renewable energy power system dominated by a high proportion of wind power, the configuration of energy storage system is an effective solution to mitigate wind power fluctuations, ensure the safe and stable operation of the grid, and improve the dispatch ability of wind power. This paper proposes a battery energy storage system (BESS) control strategy with the consideration of the impact of future wind power. To achieve maximum bidirectional output capability and minimum output of BESS, multi-objective hybrid optimization model is built on base of first-order low-pass filter’s variable time constant Tf, which contains two weight coefficients c1 and c2 to flexibly adjust BESS output. Markov chain prediction model is introduced to forecast the future multi-step wind power and PSO optimization algorithm is used to obtain the optimal BESS output power in real-time rolling calculation. Finally, the effectiveness of the proposed control strategy is verified through case studies. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Low pass filters

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Analysis of Emergency control Strategy of System Frequency under Large power Disturbance 7

Analysis of Emergency Control Strategy of System Frequency u...

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

作者： Guang, Xu Jiahe, Yang Xuelian, Wu Zhonghui, Wan Hui, Huang Fusuo, Liu Nari Group Corporation/State Grid Electric Power Research Institute State Key Laboratory of Smart Grid Protection and Control Nanjing China Nari Group Corporation/State Grid Electric Power Research Institute Power Grid Analysis and Consulting Department Nanjing China State Grid Electric Power Research Institute Nanjing China

ISBN: (纸本)9781665418195

When large-power disturbances occur in power grids, the system frequency will shift greatly, and there may be obvious spatial-temporal distribution characteristics. By analyzing the single-machine frequency response characteristics of the system and the frequency difference between the two systems, a system frequency analysis model considering nonlinear factors under large frequency difference is proposed to estimate the maximum offset of the system frequency. It is proposed to reduce the maximum frequency offset and reduce the frequency spatiotemporal distribution characteristics by selecting the coordination method of emergency control at different locations at different times, thus improving the safety and stability of the power grid. © 2022 IEEE.

关键词： Electric power transmission networks

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Energy Procurement and Retail Pricing for Electricity Retailers via Deep Reinforcement Learning with Long Short-term Memory

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CSEE Journal of power and Energy Systems 2022年第5期8卷 1338-1351页

作者： Hongsheng Xu Jinyu Wen Qinran Hu Jiao Shu Jixiang Lu Zhihong Yang State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical Electronic Engineering Huazhong University of Science and TechnologyWuhan 430074China NARI Group Corporation Nanjing 211106China School of Electrical Engineering Southeast UniversityNanjing 210096China State Key Laboratory of Smart Grid Protection and Control Nanjing 211106China

The joint optimization problem of energy procurement and retail pricing for an electricity retailer is converted into separately determining the optimal procurement strategy and optimal pricing strategy,under the“price-taker”*** aggregate energy consumption of end use customers(EUCs)is predicted to solve for the optimal procurement strategy vis a long short-term memory(LSTM)-based supervised learning *** optimal retail pricing problem is formulated as a Markov decision process(MDP),which can be solved by using deep reinforcement learning(DRL)***,the performance of existing DRL approaches may deteriorate due to their insufficient ability to extract discriminative features from the time-series vectors in the environmental *** propose a novel deep deterministic policy gradient(DDPG)network structure with a shared LSTM-based representation network that fully exploits the Actor’s and Critic’s *** designed shared representation network and the joint loss function can enhance the environment perception capability of the proposed approach and further improve the optimization performance,resulting in a more profitable pricing *** simulations demonstrate the effectiveness of the proposed approach.

关键词： Deep reinforcement learning electricity market energy procurement long short-term memory retail pricing

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