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4th IEEE Conference on Energy Internet and Energy system Integration, EI2 2020

作者： Chen, Liangliang Yang, Fengkun Xing, Qiang Wu, Shengjun Wang, Ruisheng Chen, Jiachen Electric Power Research Institute NARI Nanjing Control System Co. Ltd NARI Group Corporation/State Grid Nanjing China Southeast University School of Electrical Engineering Nanjing China State Grid Jiangsu Electric Power Co.LTD. Nanjing China Southeast University Chien-Shiung Wu College Nanjing China

ISBN: (纸本)9781728196060

Charging load prediction of electric vehicles (EVs) is an important prerequisite for studying the interaction between electric vehicles and power grid. Aiming at the influence of traffic road network information on the driving rule of EVs, a spatial-temporal distribution prediction method of charging load for EVs based on dynamic traffic information is presented. In this methodology, given the characteristic of multiple intersections in the urban road network, a dynamic road network model with the impedance of the road section and the impedance of the node are established firstly. The corresponding interactive model of transportation network-distribution network is determined according to the scale of road network. And then, the origin destination (OD) matrix analysis method and the real-time Dijkstra dynamic path search algorithm are introduced to assign start-stop nodes and plan driving paths for EVs and simulate their dynamic driving process and charging behavior. At last, the EV path planning experiment and the charging load prediction experiment in typical regions are designed to verify the effectiveness and feasibility of the proposed strategy. © 2020 IEEE.

关键词： Roads and streets

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HASN:A Hierarchical Attack Surface Network for system Security Analysis

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China Communications 2019年第5期16卷 137-157页

作者： Kangyu Huang Lin Yang Renfang Fu Shengli Zhou Zheng Hong College of Command and Control Engineering Army Engineering UniversityNanjing 210007China China Electronic Equipment & System Engineering Corporation Beijing 100141China State Grid Jiangsu Electric Power Company Research Institute Nanjing 210019China Information Department of Zhejiang Police College Hangzhou 310053China

Attack surfaces, as one of the security models, can help people to analyse the security of systems in cyberspace, such as risk assessment by utilizing various security metrics or providing a cost-effective network hardening solution. Numerous attack surface models have been proposed in the past decade,but they are not appropriate for describing complex systems with heterogeneous components. To address this limitation, we propose to use a two-layer Hierarchical Attack Surface Network(HASN) that models the data interactions and resource distribution of the system in a component-oriented view. First, we formally define the HASN by extending the entry point and exit point framework. Second, in order to assess data input risk and output risk on the HASN, we propose two behaviour models and two simulation-based risk metrics. Last, we conduct experiments for three network systems. Our experimental results show that the proposed approach is applicable and effective.

关键词： attack surface security analysis security model risk assessment

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Automated system for Measuring the Temperature of the Desiccator

Automated System for Measuring the Temperature of the Desicc...

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International Conference on Computational Problems of Electrical engineering (CPEE)

作者： Dmitro Trushakov Oleksandr Kozlovskyi Serhiy Rendzinyak Marianna Fedotova Vasyl Korud Central Ukrainian National Technical University Kropyvnytskyi Ukraine Institute of Power Engineering and Control System Lviv Polytechnic National University Lviv Ukraine

ISBN: (数字)9781728196176

ISBN: (纸本)9781728196183

The purpose of this work is to create a modern automated complex for measuring the temperature of the desiccator using modern techniques and automation elements. Research on the automation methods of the desiccator is conducted. An automated complex for measuring the temperature of the desiccator is created. A functional diagram of the thermocouple interface device with an analog-to-digital converter is developed. A low-pass filter is synthesized for noise filtering. Results of experimental studies of the automated complex with low-pass filter are provided. The introduction of integrated automation tools in the grain processing industry can significantly reduce costs and increase the output of finished products, as well as increase productivity and improve working conditions.

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Research on Fault Early Warning of Wind Turbine Pitch system based on Long Short-Term Memory Neural Network

Research on Fault Early Warning of Wind Turbine Pitch System...

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Chinese Automation Congress (CAC)

作者： Xiongwei Li Guanghua Lv Runze Zhu Gengda Li Zhongwei Lin Wenbin Wang Qingru Cui China Energy New Energy Technology Reserch Institute Co. Ltd Beijing P. R. China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control Computer and Engineering North China Electric Power University Beijing P. R. China

ISBN: (纸本)9781665426480

To reduce the downtime of wind turbine caused by the fault of pitch system that usually has a high failure rate, a fault early warning method based on long short-term memory (LSTM) neural network is proposed. According to the operation characteristics of the pitch system, monitoring parameters recorded by SCADA, such as wind speed, generator speed, rotor speed, wind direction, pitch angle and output power, are utilized to establish the fault early warning model. Compared with the model based on BP neural network, the prediction accuracy of the LSTM model is effectively improved. The weights and thresholds of the LSTM neural network are optimized, and a reasonable threshold is set to determine the fault early warning criterion for the pitch system. To verify the effectiveness of the proposed method, the LSTM model is applied to the fault early warning for a 1.5MW wind turbine pitch system. The results show that the LSTM model can give early warning about two and a half days before the fault occurs, verifying the feasibility of the proposed method.

关键词： Automation Wind speed Neural networks Rotors Predictive models Wind power generation Generators

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Erratum to: Effect of ambient pressures on laser-induced breakdown spectroscopy signals

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Frontiers of Physics 2024年第4期19卷 1-1页

作者： Zhang, Kaifan Song, Weiran Hou, Zongyu Wang, Zhe State Key Laboratory of Power System Operation and Control Tsinghua-Rio Tinto Joint Research Centre for Resources Energy and Sustainable Development International Joint Laboratory on Low Carbon Clean Energy Innovation Institute for Carbon Neutrality Department of Energy and Power Engineering Tsinghua University Beijing China Shanxi Research Institute for Clean Energy Tsinghua University Taiyuan China

The pressure legend in Fig. 6(a) was incorrectly labeled and has been updated in this new version.

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Distributed Coordinated Emergency Frequency control Strategy for Renewables-Rich power systems Based on Multi-Agent Reinforcement Learning

SSRN

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SSRN 2025年

作者： Sun, Zhenglong Han, Junpeng Chen, Weihan Zhang, Rui Liu, Yong Levron, Yoash Belikov, Juri Department of Electrical Engineering Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China The Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering Technion—Israel Institute of Technology Haifa3200003 Israel Department of Software Science Tallinn University of Technology Akadeemia Tee 15a Tallinn12618 Estonia

With the rapid growth of renewable energy in the power system and the implementation of large-capacity LCC-HVDC projects, the frequency support capability of the grid has been reduced. Simultaneously, the renewables-rich grid faces the risk of high-power shocks due to LCC-HVDC blocking. Existing centralized, single-measure approaches and the model-based emergency frequency control (EFC) methods are facing tremendous challenges. To fill this gap, this paper proposes a frequency emergency control method for renewables-rich grids that coordinates LCC-HVDC emergency power support and load shedding. The coordination of the two stabilization measures is modeled as a decentralized partially observable Markov decision process, and a multi-agent reinforcement learning (MADRL) approach is employed to optimize the power of measures for each stabilization control substation. An MADRL algorithm that integrates the system frequency response model is developed to overcome the problem of inaccurate evaluation of centralized action value in the MADRL algorithm used for EFC. This approach allows for the global optimization of the distributed coordination strategy through centralized training. The effectiveness and adaptability of the proposed method are demonstrated through simulations of the modified IEEE 39-bus system. © 2025, The Authors. All rights reserved.

关键词： Deep reinforcement learning

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Capability Analysis of Linear Extended State Observer Under Model Mismatch for LADRC control

Capability Analysis of Linear Extended State Observer Under ...

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第40届中国控制会议

作者： Yuan-Tai Chen Xian Du Si-Xin Wen Xi-Ming Sun Yan-Yan Liu School of Control Science and Engineering Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Key Laboratory of Ocean Energy Utilization and Energy Conservation (Dalian University of Technology) Ministry of Education Jiangsu Province Key Laboratory of Aerospace Power System AECC Shenyang Engine Research Institute

The Linear Extended State Observer(LESO) with model mismatch for Linear Active Disturbance Rejection control(LADRC) is investigated in this paper,which is different from the existed results that only consider the unknown *** only the uncertain disturbances in system are considered,but the model mismatch between the observer and the actual system is also *** Bounded-Input Bounded-Output stability scheme,the observer is analyzed in the time domain,and the observer error under a certain degree model mismatch is *** is proved that for LESO,the observer error caused by the model mismatch is bounded and related to the bandwidth(ω),and the error caused by model mismatch can be decreased by increasing bandwidth of the observer.

关键词： Extended State Observer model mismatch Bounded-Input Bounded-Output asymptotic stability

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Multi-channel attention mechanism graph convolutional network considering cumulative effect and temporal causality for day-ahead wind power prediction

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Energy 2025年 332卷

作者： Mao Yang Renxian Jiang Bo Wang Guozhong Fang Yunpeng Jia Fulin Fan Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin 132012 China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing 100912 China State Grid Corporation of China Northeast Branch Liaoning 100031 China Grid Jilin Electric Power Co. Ltd. Jilin Power Supply Company of State Jilin 130021 China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin 150001 China Institute for Energy and Environment University of Strathclyde Glasgow G1 1XW UK

Under the current situation where the proportion of wind power generation in the existing energy structure is gradually increasing, accurate short-term power prediction of wind farm cluster (WFC) plays an important auxiliary role in the formulation of regional power generation plans. However, it is difficult to clarify the correlation between wind farms in the power prediction of WFC, which leads to the difficulty of stable and accurate prediction. Therefore, this paper proposes a short-term power prediction method for WFC considering wind power cumulative effect (CE) and temporal causality (TC). Firstly, the two relationships (CE and TC) between wind farms are clarified and used to construct an adjacency matrix separately, then the error characteristics (EC) are used to form an adjacency matrix as well. Secondly, the adjacency matrix information with different attributes is fused by the multi-channel attention mechanism to obtain the wind power prediction results. Finally, the proposed method is applied to three WFCs in China, by which the universality and effectiveness of the method is verified. Compared with the traditional prediction method, its RMSE is reduced by 1.55 %, 1 % and 3.4 % on average.

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Conference Report: 30th power and Energy Society Annual Conference

Conference Report: 30th Power and Energy Society Annual Conf...

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作者： Kubokawa, Junji Katsube, Koji Kimura, Hiroaki Sawa, Toshiyuki Kikuchi, Kenichi Kotari, Masashi School of Technology Hiroshima Institute of Technology 2-1-1 Miyake Saiki-ku Hiroshima731-5193 Japan Power Transmission and Distribution Company Chugoku Electric Power Co. Inc. 4-33 Komachi Naka-ku Hiroshima730-8701 Japan Control System Platform Division Hitachi Ltd. 6-27-18 Minamioi Shinagawa-ku Tokyo140-8572 Japan Electric Power Engineering Research Laboratory Central Research Institute of Electric Power Industry 2-6-1 Nagasaka Yokosuka240-0196 Japan

The 30th power and Energy Society Annual Conference was held on September 3-6, 2019 at Itsukaichi Campus of Hiroshima institute of Technology in Hiroshima, Japan. The total number of presented technical papers was 409 and that of technical sessions was 50 (49 oral sessions and one poster session). A panel discussion and a special lecture were also organized during the conference period. The seats of the most events held during the period were fully occupied with audiences, and the final enrollment attained to 1,118. The conference was successfully completed with the great contribution from all the participants. This report reports the outline of the conference. © 2020 The institute of Electrical Engineers of Japan.

关键词： Energy resources

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Effect of O2 on Partial Discharge Characteristic of C5F10O/CO2 Gas Mixture

Effect of O2 on Partial Discharge Characteristic of C5F10O/C...

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Advanced Electrical Equipment and Reliable Operation (AEERO), International Conference on

作者： Yalong Xia Fan Liu Zhuo Wei Xiaoxing Zhang Pu Han Song Xiao Zhen Li Yi Li Yalong Li State Grid Sichuan Electric Power Research Institute Cheng Du China School of Electrical Engineering and Automation Wuhan University Wuhan China Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of Technology Wuhan China

ISBN: (纸本)9781665402651

C 5 F 10 O, as a new eco-friendly gas insulating medium with great application potential, has attracted much attention from researchers. There are few studies on the partial discharge (PD) characteristics of C 5 F 10 O/CO 2 O 2 gas mixture at present. In this paper, we used needle-plate electrodes to simulate the extremely inhomogeneous electric field caused by the defects of metal protrusions in electrical equipment and tested the partial discharge initial voltage (PDIV) of C 5 F 10 O/CO 2 O 2 gas mixture. The effect of oxygen on the partial discharge characteristics of C 5 F 10 O gas mixture was revealed. We found that C 5 F 10 O gas mixture has an obvious polarity effect, and PDIV + is always larger than PDIV - . The addition of oxygen reduces the PDIV - and PDIV + of C 5 F 10 O gas mixture and the reduction effect on PDIV + is more obvious. Therefore, the degrading effect of O 2 on the partial discharge characteristics of C 5 F 10 O gas mixture should be considered and the proportion of oxygen in C 5 F 10 O gas mixture should be strictly controlled.

关键词： Partial discharges Electrodes Nonuniform electric fields Insulation Electric potential Metals Voltage

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