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3rd International Conference on Electrical Engineering and control Science, IC2ECS 2023

作者： Li, Rui Zhang, Lei Lu, Yufeng Rao, Xiajin Electric Power Research Institute of Guangxi Power Grid Co. Ltd. Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Guangxi Power Grid Equipment Monitoring and Diagnosis Engineering Technology Research Center Nanning China

ISBN: (纸本)9798350382426

With the continuous development of China's power industry in recent years, China's power grid construction has developed rapidly in the context of the development of modern society. In this process, Gas Insulated Switchgear (GIS) is used in a wide range. The disconnect switch is the most frequently operated unit in GIS, and during use, the contact surface is constantly worn, resulting in a change in the contact state, which causes the abnormal temperature rise of the GIS disconnect switch. The research on the influencing factors of contact temperature is conducive to the non-invasive monitoring of contact temperature, reducing the failure of GIS disconnect switch and prolonging its service life. In this paper, a simplified model of the GIS disconnector is established, and the multi-field coupling simulation calculation of the electromagnetic-fluid-temperature field of the GIS disconnect switch is carried out, and the effects of contact resistance, ambient temperature and load current on the contact temperature are studied. The results show that the most serious temperature rise is concentrated around the contacts, and the contact temperature has an obvious functional relationship with the contact resistance, the ambient temperature and the load current, among which the contact temperature, the contact resistance and the ambient temperature satisfy the primary function relationship, and the contact temperature and the load current satisfy the quadratic function relationship. © 2023 IEEE.

关键词： contact temperature GIS disconnect switch multi-field coupling

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Optimization of Aerial Drone Visual Front-End and Multi-Sensor Fusion Localization Method 5

Optimization of Aerial Drone Visual Front-End and Multi-Sens...

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5th International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2024

作者： Zhu, Zekun Yang, Zhong Li, Tailin Zhuo, Haoze Nanjing University of Aeronautics and Astronautics College of Automation Jiangsu Nanjing China Electric Power Research Institute of Guangxi Power Grid Co. Ltd Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Guangxi Nanning China

ISBN: (纸本)9798350366174

Due to the complex environments characterized by dense equipment and strong electromagnetic interference faced by aerial electrical operations, to enhance the efficiency and safety of drone operations, this paper optimizes the front-end visual navigation system. It improves the feature extraction and matching processes by employing optical flow to track feature points during motion based on traditional ORB features, ensuring reliable localization under complex lighting and dense obstacle environments. At the backend, IMU pre-integration further corrects the visual-inertial odometry. Experimental results demonstrate that the improved visual-inertial system shows superior accuracy across multiple public datasets, and the fusion localization method enhances the aerial robot's ability to locate in complex environments. © 2024 IEEE.

关键词： Drones

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Data Fitting Method of Customer Electric Energy Consumption Based on Orthogonal Polynomial Neural Network 6

Data Fitting Method of Customer Electric Energy Consumption ...

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6th IEEE International Electrical and Energy Conference, CIEEC 2023

作者： Yu, Hong Chen, Xi Zhang, Letian Wei, Lin Yang, Linlin Wang, Zixu State Grid Jinan Power Supply Company Jinan China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China State Grid Shandong Electric Power Company Jinan China

ISBN: (纸本)9798350346671

The electric energy consumption data of marketoriented customers must be perfectly metered or accurately fitted, that is essential for the construction of electricity spot market. The electricity consumption behavior of market-oriented customers is complex and variable, to address the issue that the patterns of the electricity consumption data are difficult to be accurately characterized, an orthogonal polynomial neural network-based data fitting model of electric energy consumption is established. The model is implemented using Chebyshev orthogonal polynomials, Hermite orthogonal polynomials, Legendre orthogonal polynomials, and Laguerre orthogonal polynomials respectively, while the neural network weight coefficients are trained by gradient descent algorithm. The results show that the fitting effect of the same type of electricity consumption data differs significantly among different implementation methods. The neural network models using Hermite orthogonal polynomials and Laguerre orthogonal polynomials have higher fitting accuracy than other models. It is an effective way to achieve accurate data fitting of customer electricity consumption by selecting the corresponding fitting method according to the type of electricity consumption behavior. © 2023 IEEE.

关键词： Curve fitting

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Research on Wind Turbine control Hardware in Loop Real-time Simulation and its Application

Research on Wind Turbine Control Hardware in Loop Real-time ...

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2023 IEEE Sustainable power and Energy Conference, iSPEC 2023

作者： Zeng, Guanming Tu, Liang Zhu, Yihua Li, Chengxiang Liu, Mingqun He, Peng State Key Laboratory of HVDC and CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid National Energy Power Grid Technology R&D Centre Guangdong Provincial Key Laboratory of Intelligent Operation Control for New Energy Power System Guangdong Guangzhou China Yunnan Power Grid Co. Ltd. Electric Power Research Institute Yunnan Kunming China

ISBN: (纸本)9798350322699

With the construction of new power system, high-capacity renewable energy sources including wind power are integrated into the power system, whose transient response characteristics have a significant impact on the safe and stable operation of both renewable energy sources and power system. Real-time simulation has become an effective method to study interaction between high-capacity renewable energy sources and power system because of its high accuracy and reliability, and precise wind turbine real-time simulation model is of great significance in research mentioned above. Therefore, the wind turbine control hardware in loop (CHIL) real-time simulation method is proposed in the paper, whose feasibility and accuracy are also verified by comparing simulation data from CHIL platform and on-site testing data. It's further used in the analysis of large-scale offshore wind farm cluster and connected power system as a practical reference case. © 2023 IEEE.

关键词： control hardware in loop power system analysis real-time simulation wind turbine

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Optimization Strategy for Virtual Energy Storage of Electric Vehicles to Participate in Multiple Ancillary Services 5

Optimization Strategy for Virtual Energy Storage of Electric...

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5th International Conference on Clean Energy and Electric power Engineering, ICCEPE 2024

作者： Guo, Qi Gu, Haohan Zhao, Yifei Tu, Liang Chen, Qifang Cai, Haiqing Chen, Wei Chen, Zhihao Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou510663 China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou510663 China School of Electrical Engineering Beijing Jiaotong University Beijing100044 China

ISBN: (纸本)9798350390315

When EVs participate in multiple ancillary services of the power grid, due to the lack of a unified management scheduling plan, various ancillary service demands compete for limited energy storage resources. This would lead to conflicts when the virtual energy storage of EV participates in the regulation of multiple ancillary services. In order to solve the above problems, a reasonable and feasible optimization strategy for virtual energy storage of EVs is formulated to alleviate the conflict problems of ancillary services. The validity of the proposed method is verified by simulation cases. © 2024 IEEE.

关键词： control strategies electric vehicles multiple auxiliary services

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Response-Based Synchronization Stability Analysis of Multi-Converter power Systems 7

Response-Based Synchronization Stability Analysis of Multi-C...

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7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023

作者： Zhou, Yuren Wang, Zihan Li, Gengyin Xia, Shiwei Zheng, Le Ma, Linlin Cheng, Dingyi Wang, Ting State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources North China Electric Power University Beijing China Shandong Electric Power Dispatching and Control Center State Grid Shandong Electric Power Company Shandong China State Grid Shandong Electric Power Research Institute Power Grid Technology Center Shandong China

ISBN: (纸本)9798350345094

With the increasing integration of renewable energy into the power grid, the application of converters in the electrical systems has grown significantly. Due to the nonlinearity, the complexity and the difficult availability of the system models, traditional methods of synchronization stability analysis have revealed limitations and challenges when confronted with modern power systems. Additionally, the prevalence of grid-following converters in the grid leads to a shortage of voltage sources within the system, significantly increasing the risk of grid instability. This paper addresses the issue of synchronization stability analysis of multi-converter power systems, and proposes a response-based method to assess the synchronization stability level of the entire system. Through an analysis of the synchronization stability mechanism of grid-forming converters, a relationship is established between electromotive force, power angle, and node voltages. A quantitative stability evaluation of the system is achieved using the sBTTC index. Case studies show that the proposed response-based method is effective to analyze the synchronization stability of multi-converter power systems, with great practical viability in engineering applications. © 2023 IEEE.

关键词： Electric power system stability

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Economic dispatch of power system based on neural network algorithm 3

Economic dispatch of power system based on neural network al...

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3rd IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2023

作者： Zhu, Cheng Wan, Xiong Gu, Wei Li, Fulin Liu, Jiantao Zhang, Kaifeng Yuan, Kun Southeast University Key Laboratory of Measurement and Control of Cse Nanjing China National Electric Power Dispatching and Control Center of State Grid Corporation of China Beijing China State Grid Zhejiang Electric Power Company Hangzhou China State Grid Zhejiang Electric Power Co. Ltd. Jinhua Power Supply Company Jinhua China Nanjing China

ISBN: (纸本)9781665490788

In order to improve the absorption of new energy and quickly solve the economic dispatching problem of the power system, this paper uses neural network algorithm to build a neural network model framework to solve the unit power generation plan, cluster the load forecasting data and photovoltaic power generation data, use the improved six-node system to construct a data set, train the neural network algorithm, and finally verify the accuracy of the algorithm, providing a basis for the framework requirements in the actual project. © 2023 IEEE.

关键词： Deep learning

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Adaptive Substation Load Restoration under Extreme Hot Weather Considering the Flexibility of Air Conditioners 7

Adaptive Substation Load Restoration under Extreme Hot Weath...

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7th IEEE International Conference on power and Renewable Energy, ICPRE 2022

作者： Fan, Rui Sun, Runjia Liu, Yutian Shandong University Key Laboratory of Power Grid Intelligent Dispatch and Control of Ministry of Education Jinan China

ISBN: (数字)9781665450638

ISBN: (纸本)9781665450638

Load restoration fitting to the change of load amount, available power and outdoor temperature is an important measure to enhance power system resilience under extreme hot weather. A multi-time scale substation load restoration method considering active control of air conditioners is proposed for adaptive restoration. First, a framework of adaptive load restoration is formulated to coordinate the longtime scale whole process scheme making and short-time scale active air conditioners control. Second, an optimization model considering the whole process of substation load restoration is established to make feeder switch schemes to improve load restoration efficiency from the perspective of a long-time scale. Third, model predictive control is adopted to realize the active control of air conditioners from the perspective of a short-time scale to fit the continuously changed load amount, available power and outdoor temperature during restoration. The simulation results demonstrate that the proposed substation load restoration method can make schemes adaptively with better restoration benefit under extreme hot weather. © 2022 IEEE.

关键词： Restoration

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Identification of hidden danger discharges in transmission lines based on multi-scale convolutional neural network 3

Identification of hidden danger discharges in transmission l...

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2024 3rd International Conference on Smart grid and Green Energy, ICSGGE 2024

作者： Huang, Zhidu Huang, Wei Liu, Yinglong Chen, Yajuan Li, Shengdong Guangxi Key Laboratory of Intelligent Control and Operation and Maintenance of Power Equipment Electric Power Research Institute of Guangxi Power Grid Co. Ltd. Guangxi Zhuang Autonomous Region Nanning530023 China Nanning Power Supply Bureau of Guangxi Power Grid China Southern Power Grid Guangxi Zhuang Autonomous Region Nanning530021 China Beihai Power Supply Bureau of Guangxi Power Grid China Southern Power Grid Guangxi Zhuang Autonomous Region Beihai536006 China

The presence of hidden dangers in transmission lines poses a significant threat to the safe and stable operation of the power grid. Timely identification of these hidden dangers is crucial to simplify maintenance tasks for the operation department. This paper introduces a model based on a Multi-Scale Convolutional Neural Network (MSCNN) to identify the discharge types of hidden dangers in transmission lines. Initially, the Intrinsic Mode Functions (IMFs) of the hidden danger discharge signal measured from the transmission line are obtained through Variational Mode Decomposition (VMD). Subsequently, multi-scale time-frequency features within the IMFs are extracted by MSCNN. Finally, a Softmax classifier completes the task of identifying the type of hidden danger discharge. The training and testing results of the model demonstrate that its accuracy in identifying the four types of hidden dangers researched in this paper can reach 90.38%. © Published under licence by IOP Publishing Ltd.

关键词： Convolutional neural networks

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Prediction-based dynamic routing intelligent algorithm in power optical communication network

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The Journal of China Universities of Posts and Telecommunications 2022年第6期29卷 46-52页

作者： Guo Xuerang Li Feng Zhu Bohan Zhang Zhijun Guo Qingrui Yang Huiting Electric Power Research Institute State Grid Xinjiang Electric Power Co.Ltd.Urumqi 830000China State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijing 100876China Dispatching and Control Center State Grid Xinjiang Electric Power Co.Ltd.Urumqi 830000China

New energy power generation equipment has the characteristics of diurnal, perturbative, seasonal, and periodic power generation, which makes new power optical communication network(POCN) more dynamic and changeable. This is directly reflected in the dynamics of the link risk and service importance of the POCN. In this paper, aiming at the problem of the dynamic importance of service in POCN, and the resulting power optical communication network reliability decline problem, a new energy POCN dynamic routing intelligence algorithm based on service importance prediction is proposed. Based on the short-term power generation of new energy power station, the importance of each service and the risk degree of each link are predicted. Link weights are dynamically adjusted, and k-shortest path(KSP) algorithm is used to calculate route results. When network resources are insufficient, low-importance services can give way to prevent a large number of high-importance services from being blocked. Simulation results show that compared with the traditional KSP algorithm, the prediction-based dynamic routing intelligent(P-DRI) algorithm can reduce the service blocking probability by 55.59%, and reduce the average importance of blocking services by 44.77% at the cost of about 6.17% of the calculation delay.

关键词： new power optical communication network(POCN) traffic diversion new energy power generation network risk degree

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