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Annual Meeting of CSEE Study Committee of HVDC and power Electronics (HVDC 2023)

作者： S. Li Y. Hu X. He Y. Zhu T. He C. Luo C. Deng G. Zeng M. Su Yunnan Electric Power Research Institute Kunming People's Republic of China National Energy Power Grid Technology R&D Centre Guangzhou People's Republic of China State Key Laboratory of HVDC Electric Power Research Institute CSG Guangzhou People's Republic of China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou People's Republic of China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou People's Republic of China

With the increase of wind and solar renewable energy penetration in power system, the frequency control ability of power system completely depending on traditional power supply has weakened. This actuality requires that renewable energy stations should be equipped with a certain amount of energy storage to improve the primary frequency control ability. This paper considers the fast response ability and flexible control of energy storage for both charging and discharging, as well as its unique frequency response characteristics. Firstly, the control characteristics of the primary frequency regulation of the hybrid wind-solar-storage power station(Wind-PV-ES) are analyzed. By improving the automatic generation control(AGC) strategy of the hybrid Wind-PV-ES power station, a coordinated control strategy for the primary frequency regulation of the hybrid Wind-PV-ES power station is proposed for different frequency ranges based on the improved AGC control. After the primary frequency regulation action, the energy storage output is given priority control before wind and solar. When the energy storage active margin is insufficient, use the frequency regulation capacity of wind and photovoltaic power system to improve the primary frequency regulation capacity of the hybrid Wind-PV-ES power station. The control strategy proposed in this paper can improve the primary frequency regulation capability of renewable energy station. Finally, the paper verifies the effectiveness of the proposed control strategy through simulation.

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Precise regulation of acid pretreatment for red mud SCR catalyst:Targeting on optimizing the acidity and reducibility

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Frontiers of Environmental Science & Engineering 2022年第7期16卷 61-71页

作者： Xiang Zhang Yue Xuan Bin Wang Chuan Gao Shengli Niu Gaiju Zhao Dong Wang Junhua Li Chunmei Lu John C.Crittenden National Engineering Laboratory for Coal-Burning Pollutants Emission Reduction School of Energy and Power EngineeringShandong UniversityJinan250061China School of Civil and Environmental Engineering and the Brook Byers Institute for Sustainable Systems Georgia Institute of TechnologyAtlantaGA30332USA State Key Joint Laboratory of Environment Simulation and Pollution Control National Engineering Laboratory for Multi Flue Gas Pollution Control Technology and EquipmentSchool of EnvironmentTsinghua UniversityBeijing100084China Energy Institute Qilu University of Technology(Shandong Academy of Sciences)Jinan250013China

Red mud(RM),as an alkaline waste,was recently proved to be a promising substitute for the SCR *** could improve the acidity and reducibility of red mud,which were critical for SCR ***,the dealkalization effect depended on the reaction between acid solution and red *** this study,we realized the directional control of the chemical state of active sites through tuning the acid pretreatment(dealkalization)*** pretreatment endpoint was controlled at pH values of 3–5 with diluted nitric *** the pH values of red mud were 3 and 5(CRM-3 and CRM-5),activated catalysts showed NOx conversion above 90%at 275℃–475℃.The high initial reaction rate,Ce^(3+)/(Ce^(3+)+Ce^(4+))ratio,and surface acidity accounted for the excellent SCR performance of CRM-5 ***,more Fe^(3+) on the CRM-3 surface improved the NH_(3) *** was a strong interaction between Al and Fe in both CRM-5 and CRM-3 *** results showed that the adsorption capacity of the Al-O_(3)-Fe for NH_(3) and NO is stronger than that of Fe-O_(3)-Fe,which enhanced the NOx conversion of the ***,the almandine was formed in CRM-4,consumed part of Fe^(3+) and Al^(3+),and the interaction between Al and Fe was ***,deposited almandine on the catalyst surface covered the active sites,thus leading to lower NH_(3)-SCR activity.

关键词： Air pollution control Nitrogen oxides Selective catalytic reduction Red mud Solid waste utilization

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Wide-Area Damping control Enhanced by Non-Invasive Data Verification Against False Data Injection Attacks

SSRN

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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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Dynamic Security Assessment Method of power system Based on Improved XGBoost 3

Dynamic Security Assessment Method of Power System Based on ...

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2020 3rd International Conference on Mechanical, Electrical and Material Application, MEMA 2020

作者： Ren, Jihong Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin Jilin132012 China Department of Electrical Engineering Northeast Electric Power University Jilin Jilin132012 China

With the deployment of wide-area measurement systems (WAMS) equipment, dynamic security assessment (DSA) based on artificial intelligence (AI) has more and more advantages. For the power system, the number of transient stable cases is much larger than that of unstable cases, which leads to insufficient learning of unstable cases and affects the evaluation effect of the model. In addition, during the stability assessment process of the power system, the misjudgment cost of unstable case is much higher than that of stable case. Based on the above two points, we proposed a DSA method of power system based on improved XGBoost. The proposed method introduces the weight adjustment factor into the loss function to balance the quantity variance of two type cases and the difference of misjudgment cost, which greatly reduces the misjudgment rate of unstable samples. The test results on IEEE 16-machine 68-bus test system and IEEE 50-machine 145-bus test system show that the proposed method can have higher recognition of the unstable samples and can be applied to DSA. © Published under licence by IOP Publishing Ltd.

关键词： system stability

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Disturbance event classification and regional localization in interconnected power grids based on the S-Koopman energy matrix

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Dianli Xitong Baohu yu Kongzhi/power system Protection and control 2025年第11期53卷 105-115页

作者： Zhou, Shuyu Yang, Jingying Cai, Guowei Liu, Cheng Jiang, Chao Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Grid Jilin Electric Power Co. Ltd. Changchun132000 China

The classification of disturbance event types and the identification of their regional locations are critical for the stability analysis and control of interconnected power grids. To address this, a disturbance event classification and localization method based on the S-Koopman energy matrix is proposed. This method uses the subspace optimal mode decomposition algorithm (Sub-OpMD) to calculate the optimal low dimensional matrix of the S-Koopman operator, which captures the dynamic information of the stochastic system. The S-Koopman energy matrix is then constructed according to the eigen decomposition results of the optimal low dimensional matrix. The S-Koopman energy matrix reflects the dynamic behavior of the system;its row/column vectors can extract different feature data following disturbance events, as well as the fluctuation strengths of PMU data at different positions. Furthermore, by analyzing the dynamic variation patterns of PMU data under different disturbance types and regions, quantitative indicators of disturbance event classification and regional localization are proposed. The calculation and analysis of the New England 10-generator 39-bus simulation system and the CEPRI-SSFS 197-bus real-world system verify the rationality, effectiveness, and accuracy of the proposed method. © 2025 power system Protection and control Press. All rights reserved.

关键词： Electric power system protection

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Two-step Optimal Allocation of Stationary and Mobile Energy Storage systems in Resilient Distribution Networks

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Journal of Modern power systems and Clean Energy 2021年第4期9卷 788-799页

作者： Xinyi Jiang Jian Chen Qiuwei Wu Wen Zhang Yicheng Zhang Jie Liu Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan 250061China Center for Electric Power and Energy(CEE) Department of Electrical EngineeringTechnical University of Denmark(DTU)2800 Kongens LyngbyDenmark Institute for Infocomm Research(I2R) Agency for ScienceTechnology and Research(A*STAR)Singapore State Grid Yantai Power Supply Company YantaiChina

Energy storage systems (ESSs) are acknowledged to be a promising option to cope with issues in high penetration of renewable energy and guarantee a highly reliable power supply. In this paper, a two-step optimal allocation model is proposed to obtain the optimal allocation (location and size) of stationary ESSs (SESSs) and mobile ESSs (MESSs) in the resilient distribution networks (DNs). In the first step, a mixed-integer linear programming (MILP) problem is formulated to obtain the preselected location of ESSs with consideration of different scenarios under normal operation conditions. In the second step, a two-stage robust optimization model is established to get the optimal allocation results of ESSs under failure operation conditions which are solved by column-and-constraint generation (C&CG) algorithm. A hybrid ESS allocation strategy based on the subjective and objective weight analysis is proposed to give the final allocation scheme of SESSs and MESSs. Finally, the proposed two-step optimal allocation model is demonstrated on a modified IEEE 33-bus system to show its effectiveness and merits.

关键词： Resilient distribution network stationary energy storage system mobile energy storage system optimal allocation

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A Quasi-Parallel Resonant Switched Capacitor DC-DC Converter with Wide Input Voltage Range Regulation and Enhanced Dynamic Performances

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IEEE Journal of Emerging and Selected Topics in power Electronics 2025年

作者： Qi, Jingjing Wu, Xuezhi Sun, Kai Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing100084 China Beijing Jiaotong University National Active Distribution Network Technology Research Center Beijing100044 China

Wide-range and high-efficiency DC-DC converters are in high demand for various applications, such as distributed systems, electric vehicles, and DC buildings. Resonant switched capacitor converters (ReSCC) can achieve soft switching, have small passive device capacity, and exhibit low voltage stress, but the voltage ratio is difficult to be regulated continuously. In this paper, a quasi-parallel resonant switched capacitor DC-DC converter is proposed to satisfy the design requirements, which incorporates a ReSCC with soft-switching and variable voltage ratio, as well as a Buck converter. In addition, a simplified optimal trajectory controller for ReSCC is investigated, which can be combined with PI controller of Buck converter to enhance the load transient of the proposed converter. Moreover, the input voltage feedforward control is implemented with the optimized feedforward coefficient to suppress the input voltage disturbance. The proposed converter can achieve high efficiency and rapid dynamic response over a wide conversion range. The correctness of the theoretical analyses is verified by a 36V∼60V-5V/20A prototype. © 2013 IEEE.

关键词： Capacitor bank

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Short-term power load forecasting method based on CNN-SAEDN-Res

arXiv

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arXiv 2023年

作者： Cui, Yang Zhu, Han Wang, Yijian Zhang, Lu Li, Yang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China College of Information and Electrical Engineering China Agricultural University Beijing100083 China

In deep learning, the load data with non-temporal factors are difficult to process by sequence models. This problem results in insufficient precision of the prediction. Therefore, a short-term load forecasting method based on convolutional neural network (CNN), self-attention encoder-decoder network (SAEDN) and resi- dual-refinement (Res) is proposed. In this method, feature extraction module is composed of a two-dimensional convolutional neural network, which is used to mine the local correlation between data and obtain high-dimensional data features. The initial load fore-casting module consists of a self-attention encoder-decoder network and a feedforward neural network (FFN). The module utilizes self-attention mechanisms to encode high-dimensional features. This operation can obtain the global correlation between data. Therefore, the model is able to retain important information based on the coupling relationship between the data in data mixed with non-time series factors. Then, self-attention decoding is per-formed and the feedforward neural network is used to regression initial load. This paper introduces the residual mechanism to build the load optimization module. The module generates residual load values to optimize the initial load. The simulation results show that the proposed load forecasting method has advantages in terms of prediction accuracy and prediction stability. Copyright © 2023, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Tuning the oxidation state of Ru to surpass Pt in hydrogen evolution reaction

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Nano Research 2021年第11期14卷 4321-4327页

作者： Rongpeng Ma Ying Wang Guoqiang Li Long Yang Shiwei Liu Zhao Jin Xiao Zhao Junjie Ge Wei Xing State Key Laboratory of Electroanalytical Chemistry Laboratory of Advanced Power SourcesChangchun Institute of Applied ChemistryChinese Academy of SciencesChangchun130022China School of Applied Chemistry and Engineering University of Science and Technology of ChinaHefei230026China State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchun130022China State Key Laboratory of Automotive Simulation and Control School of Materials Science and Engineering Key Laboratory of Automobile Materials of MOEJilin UniversityChangchun130012China

The high price of state-of-the-art Pt electrocatalysts has plagued the acidic water electrolysis technique for decades. As a cheaper alternative to Pt, ruthenium is considered an inferior hydrogen evolution reaction (HER) catalyst than Pt due to its high susceptibility to oxidation and loss of activity. Herein, we reveal that the HER activity on Ru based catalysts could surpass Pt via tuning Ru oxidation state. Specifically, RuP clusters encapsulated in few layers of N, P-doped carbon (RuP@NPC) display a minimum over potential of 15.6 mV to deliver 10 mA·cm^(−2). Moreover, we for the first time show that a Ru based catalyst could afford current density up to 4 A·cm^(−2) in a practical water electrolysis cell, with voltage even lower than the Pt/C-based cell, as well as high robustness during 200 h operation. Using a combination of experiment probing and calculation, we postulate that the suitably charged Ru (∼ +2.4) catalytic center is the origin for its superior catalytic behavior. While the moderately charged Ru is empowered with optimized H adsorption behavior, the carbon encapsulation layers protect RuP clusters from over oxidation, thereby conferring the catalyst with high robustness.

关键词： RuP clusters Ru oxidation state hydrogen evolution encapsulating/confining layers

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Case Study of Microgrid Operation in the Context of Environment and Energy Storage

Case Study of Microgrid Operation in the Context of Environm...

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International Conference on power and Energy Technology (ICPET)

作者： Shen Na Li Shuyong Guo Changxin Han Fengqin Cai Haiqing School of Electrical Engineering Guangzhou City University of Technology Guangzhou City China State Key Laboratory of HVDC China Southern Power Grid Electric Power Research Institute Co. Ltd. Guangzhou City China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou City China

ISBN: (数字)9798350375855

ISBN: (纸本)9798350375862

The global energy crisis and environmental crisis have led to the rapid development of new energy, especially in the context of China's dual carbon strategy target in 2020, the next few decades, the new energy industry in China's energy structure will account for an increasingly high proportion. In order to support the realization of the "double carbon" goal, wind power, photovoltaic and other new energy will play an irreplaceable role. However, a large number of new energy sources connected to the power grid will have some impact on the characteristics of the power system. In order to study the operating characteristics of multiple new energy sources connected to the microgrid, this paper builds a microgrid control simulation platform containing various distributed power sources such as solar, wind, small hydropower, thermal voltaic, and energy storage. The simulation platform is used to study the operating characteristics of various new energy sources in different seasons, load changes and storage capacity changes. The results show that the power output of various new energy sources is influenced by environmental factors, especially photovoltaic, wind power and thermal voltages; energy storage capacity also has an impact on the microgrid system. The research results provide theoretical support for the intelligent control and integrated management of microgrid with multiple new energy sources.

关键词： Photovoltaic systems Wind Thermal factors Microgrids Wind power generation Real-time systems Environmental factors Carbon Energy storage Intelligent control

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