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

作者： Huang, Ying Lu, Yuanhong Zhao, Yanjun Hu, Yufeng Zhang, Jie Guo, Haiping China Southern Power Grid State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou Guangzhou510663 China China Southern Power Grid National Energy Power Grid Technology R & D Centre 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 CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou Guangzhou510663 China

ISBN: (纸本)9798331532765

The fault transient characteristics of power grids have undergone a fundamental transformation as a consequence of the advent of hybrid scale access to power grids by new energy sources. Nevertheless, the existing stand-alone equivalent model is unable to accurately characterise the fault transient characteristics of the hybrid light-water-wind electric field/cluster. Furthermore, the simulation computation of the stand-alone equivalent model is considerable in scale and the simulation efficiency is low. This paper proposes a particle swarm neural network-based clustered equivalent modelling method for a light-water-wind hybrid electric field. Firstly, a transient model of the light-water-wind hybrid electric field is established, and the characteristic influence factors of faults are constructed through theoretical analysis. These include the distance between the light-water-wind hybrid electric field and the point of common coupling (PCC), the input of current limiting measures on the DC side, the light, the water speed, the wind speed, and the reactive power at the outlet. Subsequently, the Euclidean distance is calculated for the set of characteristic influencing factors, and the initial centre of clustering of wind turbines is extracted based on the improved maximum-minimum distance method. Ultimately, the clustering equivalent modelling is accomplished through the utilisation of the aforementioned feature influencing factors and the classification initial centre as the training set. The simulation results show that compared with the single-machine equivalent model, The simulation error has been reduced from the order of magnitude of 10-2 p.u. to the order of magnitude of 10-4 p.u., while the simulation efficiency of this method is has been reduced from the order of magnitude of 10-2 s to the order of magnitude of 10-4 s. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Spatial-Temporal Attention Mechanism and Graph Convolutional Networks Based Distributed PV Ultra-short-term power Forecasting

Spatial-Temporal Attention Mechanism and Graph Convolutional...

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2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

作者： Liu, Xinyu Xie, Xu Fang, Qin Xu, Fei Huang, Chen Zhen, Zhao Wang, Fei State Grid Chongqing Electric Power Company Chongqing400015 China Shinan Power Supply Branch State Grid Chongqing Electric Power Company Chongqing China Tsinghua University State Key Laboratory of Power System Operation and Control Beijing100084 China North China Electric Power University Department of Electrical Engineering Baoding071003 China

ISBN: (纸本)9781665471640

To ensure the efficient operation and healthy development of photovoltaic power generation systems, reliable distributed photovoltaic power prediction is significant. However, the lack of modeling ability of existing distributed photovoltaic power forecasting methods for dynamic spatiotemporal correlation of distributed photovoltaic power data limits the further improvement of prediction accuracy. Therefore, a distributed photovoltaic ultra-short-term power forecasting method based on spatial-temporal attention mechanism and graph convolutional networks is proposed in this paper. Firstly, distributed photovoltaic cluster is divided into sub-regions and graph structured data can be generated with each sub-region being a node on the graph. Then, spatial-temporal attention mechanism is used to adaptively capture spatiotemporal correlation information and dynamically update adjacency matrix. Finally, spatial-temporal convolution is used to extract deep spatiotemporal features of distributed photovoltaic power data and achieve regional power prediction. The validity and progressiveness of the model have been verified in real world data sets. © 2023 IEEE.

关键词： distributed photovoltaic graph convolutional networks spatial-temporal attention mechanism ultra-short-term power forecasting

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Cyber-Attack Risk Assessment and Prevention Strategy of Substations Based on Dynamic Attack and Defense Game 3

Cyber-Attack Risk Assessment and Prevention Strategy of Subs...

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3rd power system and Green Energy Conference, PSGEC 2023

作者： Lin, Feng Mei, Yong Zhu, Yihua Chang, Dongxu Liu, Ren Guo, Hengdao China Southern Power Grid Power Dispatch and Control Center GuangZhou China Electric Power Research Institute China Southern Power Grid State Key Laboratory of Hvdc GuangZhou China Electric Power Research Institute China Southern Power Grid National Energy Power Grid Technology R&d Centre GuangZhou China China Southern Power Grid Csg Key Laboratory for Power System Simulation GuangZhou China Guangdong Provincial Key Laboratory of Intelligent Operation Control for New Energy Power System GuangZhou China

ISBN: (纸本)9798350340099

With the improvement of the informatization of the power system, the risk of cyber attack is also increasing. This paper proposes a risk assessment and prevention strategy for cyber attack against substations. Firstly, the cyber attack against substations are modeled based on the game theory of dynamic attack and defense. Secondly, an improved OPA (ORNL-PSERC-Alaska) model is utilized to analyze the cascade failure after cyber attacks and quantify the load loss of power system. Finally, a preventive strategy which can mitigate the expectation load loss caused by cyber attack against substations is put forward. Simulation experiments were conducted to validate the effectiveness of the proposed method. © 2023 IEEE.

关键词： Risk assessment

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A capacitor-type DC circuit breaker for offshore all-DC grids 4

A capacitor-type DC circuit breaker for offshore all-DC grid...

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

作者： Xu, Qianqian Liu, Qihui Cai, Xipeng Zhu, Yihua Luo, Chao North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing China National Energy Power Grid Technology R&d Centre Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&d Centre Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9798331518066

Full DC of offshore wind farms is the future development trend of large-scale offshore wind farms, however, the probability of DC line faults is high, and the use of DC circuit breakers can realise the fault ride-through of offshore full DC wind farms, improve the safe operation of the system during faults, and is one of the mainstream solutions to realise DC fault isolation. In this paper, a capacitive DC circuit breaker suitable for offshore full DC grid is proposed, which can effectively suppress the fault current by introducing a current limiting device. The topology and working principle of this circuit breaker are analysed, and the circuit breaker fault handling process is theoretically analysed. Finally, for the single-end equivalent system using capacitor-type DC circuit breaker, a simulation model is established in Matlab/Simulink software for verification, and the simulation results show that the proposed circuit breaker has a better current limiting effect and has the ability to isolate faults quickly. © 2024 IEEE.

关键词： Offshore wind farms

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Non-unit protection for HVDC grids based on wavelet analysis of transient voltage

Non-unit protection for HVDC grids based on wavelet analysis...

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18th International Conference on Developments in power system Protection (DPSP APAC 2025)

作者： Xinyuan Li Boliang Jin Zhenkang Qi Binshu Chen Xinzhou Dong State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing People's Republic of China

ISBN: (数字)9781837242900

DC grids utilizing MMC-HVDC technology have been extensively researched and implemented in various locations, demonstrating substantial benefits in terms of system flexibility and renewable energy integration. Due to the rapid escalation of fault currents, DC line protections must quickly identify and isolate faults, typically within milliseconds, leading to the adoption of non-unit methods as the primary protection. This paper introduces a non-unit protection scheme that employs transient voltage at both the line-side and converter-side of the supplemental inductor. Based on a reduced model focusing on the boundary of a DC line, the transient process of the fault is examined using traveling wave theory, and the voltage characteristics at both ends of the supplemental inductor are scrutinized. The theoretical analysis also brings out a practical method for threshold-value calculation. Then, a protection criterion, based on wavelet analysis of the transient voltage, is established. This proposed method is capable of fulfilling the requirements for speed, selectivity and fault resistance and has been verified through PSCAD/EMTDC simulations.

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Nonlinear E-field Simulation of HVDC Converter Transformer Busing and Its Structure Optimization With RBF Neural Network and NSGA-II Algorithm 13

Nonlinear E-field Simulation of HVDC Converter Transformer B...

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13th International Conference on power and Energy systems, ICPES 2023

作者： He, Yongsheng Zhang, Shiling Lu, Zongxiang Wang, Pengbo State Grid Chongqing Electric Power Company Chongqing Electric Power Research Institute Chongqing China State Key Lab of Control and Simulation of Power Systems and Generation Equipment Haidian China Transmission Equipment and System Security and New Technology Dept Name of State Key Laboratory of Power Chongqing China

ISBN: (纸本)9798350345063

Static DC and PR are typical operation conditions of HVDC converter transformer bushing outlet device, moreover, the electrical parameters of RIP, transformer oil and OIP have the nonlinear relationship with E-field stress and temperature. Under the temperature gradient, the electrical parameters will modify the static DC and PR E-field distribution of the composite insulation. In order to simulate static DC and PR electric field of the composite insulation structure, this paper established the full model of the converter transformer outlet. Then, the structure parameters of converter transformer outlet have been optimized using combined RBF neural network and NSGA-II algorithm. Moreover, electric field verification calculation has been carried out under AC and PR conditions. The results show that under uniform temperature condition, E-field strength is larger than that under iso-thermal condition. The overshoot coefficient of the bushing end and barrier reach 65% and 45%, respectively. The study can provide reference for the design of outlet structure of the converter transformer. © 2023 IEEE.

关键词： DC transformers

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STDHL: Spatio-Temporal Dynamic Hypergraph Learning for Wind power Forecasting

arXiv

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arXiv 2024年

作者： Dong, Xiaochong Zhang, Xuemin Yang, Ming Mei, Shengwei State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing100084 China Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan250061 China

Leveraging spatio-temporal correlations among wind farms can significantly enhance the accuracy of ultra-short-term wind power forecasting. However, the complex and dynamic nature of these correlations presents significant modeling challenges. To address this, we propose a spatio-temporal dynamic hypergraph learning (STDHL) model. This model uses a hypergraph structure to represent spatial features among wind farms. Unlike traditional graph structures, which only capture pair-wise node features, hypergraphs create hyperedges connecting multiple nodes, enabling the representation and transmission of higher-order spatial features. The STDHL model incorporates a novel dynamic hypergraph convolutional layer to model dynamic spatial correlations and a grouped temporal convolutional layer for channel-independent temporal modeling. The model uses spatio-temporal encoders to extract features from multi-source covariates, which are mapped to quantile results through a forecast decoder. Experimental results using the GEFCom dataset show that the STDHL model outperforms existing state-of-the-art methods. Furthermore, an in-depth analysis highlights the critical role of spatio-temporal covariates in improving ultra-short-term forecasting accuracy. Copyright © 2024, The Authors. All rights reserved.

关键词： Wind forecasting

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Study of improved active-clamped phase shift full bridge converter

Study of improved active-clamped phase shift full bridge con...

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Electrical Engineering and control Science (IC2ECS), International Conference on

作者： Xin He Runquan Meng Ruishu Li Shanxi Key Lab of Power System Operation and Control Taiyuan University of Technology Taiyuan China

Aiming at the drawbacks of the conventional phase-shifted full-bridge topology in terms of high voltage stress in the synchronous rectifier switches and high switching loss of the primary-side switch under low load conditions, a phase-shifted full-bridge circuit with improved control of an active clamp circuit is proposed. The converter utilizes the resonance of the switch parasitic capacitance with the primary-side resonant inductor to achieve ZVS (Zero- Voltage-Switch) under light load, and effectively improves the efficiency under heavy load by zeroing the primary-side current in the circulating current stage. In this paper, the topology, operating principle and operating characteristics of the proposed scheme are described in detail, and the feasibility of the scheme is verified by simulation in PLECS platform.

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MCMC Wind power Sequence Modeling Method Considering Climbing Direction

MCMC Wind Power Sequence Modeling Method Considering Climbin...

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2023 IEEE International Conference on power Science and Technology, ICPST 2023

作者： Hao, Ling Xu, Fei Chen, Lei Chen, Qun Min, Yong Gu, Yi Chang, Yiming State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing100084 China Tsinghua University Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Engineering Mechanics Beijing100084 China State Grid Liaoning Electric Power Co. Ltd Liaoning 110055 China

ISBN: (纸本)9798350311358

Since the traditional Markov Chain Monte Carlo (MCMC) method has the problem that the wind power is stuck in a certain state and it is difficult to jump, this paper proposes an improved MCMC method considering the climbing direction, first dividing the state by the size of the output and the climbing direction, and then determining the duration of each state by changing the state, and then sampling and generating the corresponding number of output samples according to the duration of each state, and sorting these samples according to the climbing direction, and the sorted output is the output timing of the state. This method was used to generate wind power sequences from a wind farm in the Northeast China Sea, and the characteristics of a wind power sequence were compared and analyzed with the original wind power sequence, and the results were better than the wind power sequences generated by the traditional MCMC method. © 2023 IEEE.

关键词： Wind power

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Research on 220kV Spare power Automatic Switching Equipment Standardized Application of Local functions Based on Real-Time Simulation∗ 5

Research on 220kV Spare Power Automatic Switching Equipment ...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Huang, Zhida Wu, Wencong Cai, Haiqing Zhu, Yihua Huang, Libin Chang, Dongxu State Key Laboratory of Hvdc Electric Power Research Institute Csg National Energy Power Grid Technology R&d Centre Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Csg Key Laboratory for Power System Simulation Guangzhou China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

Currently, the power grid is carrying out the standardized design and application of 220kV spare power automatic switching equipment. It is more difficult to carry out the on-site standby automatic switching function test in the actual power grid. The power supply department urgently needs a simulation environment that can truly simulate the actual power grid to support the development of this functional test. Real-time simulation has the ability to carry out on-site automatic transfer function tests in terms of technical feasibility. To verify its effectiveness, this paper built a standardized closed-loop test system for 220kV spare power automatic switching equipment based on real-time simulation. A number of tests have been carried out for the automatic switch-on function of on-site equipment, and the device action events on the actual site have been inverted. The test results show that the established RTDS real-time simulation model has the ability to simulate the actual 220kV power grid. It has been verified that the action logic of the standby automatic input device in various modes meets the requirements of the standard specification, which strongly supports the standardized application of the 220kV spare power automatic switching equipment function of the power grid. © 2022 IEEE.

关键词： Switching

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