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International Conference of Electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Yu, Jiawei Zhu, Yihua Zhou, Yini Hu, Bo Li, Zheyu Li, Xiaoyu State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou510663 China State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789819620418

The large-scale access of wind power causes a significant reduction in the inertia of the power system, seriously threatening the security and stability of the system frequency. Inertia control methods based on the optimized PLLs provide a solution to the low inertia problem of doubly-fed inductance generator (DFIG)-based wind turbines (WTs), but they still suffer from poor dynamic performance and obvious phase-locked error in steady state. For this reason, a novel inertia control method for DFIG-based WTs is proposed in this paper to support the system frequency with better performance in all aspects. Firstly, an equivalent inertia model is deduced considering the dynamic of control and the reason why modifying PLL can realize inertia response of WT is analyzed. Then, the existing inertia control methods based on optimized PLL is introduced and a novel inertia control method with phase-locked error feed-forward in PLL (pefPLL) is proposed. After that, the inertia characteristics, dynamic performance, and steady state performance of pefPLL and other PLLs are compared. Finally, the superiority of the novel inertia control method with pefPLL is verified by simulations. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Wind turbines

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LEUSIM: A Lightweight Extendable User SIMulator for Testing Commercial Task-Oriented Dialogue System

LEUSIM: A Lightweight Extendable User SIMulator for Testing ...

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2025 International Conference on Electrical Automation and Artificial Intelligence, ICEAAI 2025

作者： Li, Xiaoqian Guan, Wenbo Liang, Lingyu Zhang, Huanming School of Computing Science and Engineering South China University of Technology Guangzhou China Institute of Information Engineering Chinese Academy of Sciences Beijing China Artificial Intelligence Technology Co. Ltd China Southern Power Grid Guangzhou China

ISBN: (纸本)9798331506797

We propose LEUSIM (Lightweight Extendable User SIMulator), an automatic testing and assessing framework for commercial Chinese task-oriented dialogue systems. LEUSIM contains four modules, namely, natural language parser, business flow controller, user utterance imitator and system performance recorder, which can be directly obtained from the existing telephone intelligent customer service (TICS) system without or with a little adaptation. Having dependency parsing theory as its theoretical basis, LEUSIM can fully imitate the users' behavior and make it an applicable testing framework in real world scenario. © 2025 IEEE.

关键词： Commercial task-oriented dialogue system dependency parsing theory testing framework

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Research on the Design of UAV Relay Charging High-rise Platform for Electrical Equipment Live Detection in Substation 2

Research on the Design of UAV Relay Charging High-rise Platf...

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2022 2nd International Conference on Energy, power and Electrical Engineering, EPEE 2022

作者： Zhang, Yanyan Ning, Xuefeng Zhang, Haipeng Yang, Youhang Wang, Shaorong China Southern Power Grid Dongguan Power Supply Bureau Guangdong Dongguan China School of Electrical and Electronic Engineering Huazhong University of Science and Technology Hubei Wuhan China

The multi-rotor UAV inspection technology has received extensive attention in the live detection of electrical equipment in substations and has begun to be practically applied. However, due to the short endurance and the characteristics of intermittent operations, the UAV needs to frequently travel between the operational airspace and the cabin, which seriously affects the operational efficiency of the inspection. This paper first introduces the traditional substation electrical equipment live detection technology and then summarizes the application of UAV inspection in the substation electrical equipment live detection. Finally, in view of the shortcomings of the existing technology, this paper proposes a design scheme of a relay-charging high-rise platform for live detection and inspection of electrical equipment in substations. The relay charging high-rise platform can be divided into six parts according to the functional structure: high-altitude apron, UAV landing guidance system, UAV automatic binding system, high insulation strength power supply system, and platform monitoring system. In this paper, the overall structure of the relay charging high-level platform and the technical solutions of each component are described in detail. The technical solution can effectively improve the efficiency and safety of multi-rotor UAV inspection operations for live detection of electrical equipment in substations. © Published under licence by IOP Publishing Ltd.

关键词： Unmanned aerial vehicles (UAV)

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CoFMD-BiLSTM: A Wind and Photovoltaic power Prediction Method Based on Feature Mode Decomposition and Cooperative Learning Strategy

CoFMD-BiLSTM: A Wind and Photovoltaic Power Prediction Metho...

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2024 china Automation Congress, CAC 2024

作者： Ding, Xinzhi Li, Dayi Huang, Wei Chen, Yiping State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China Co. Kunming650217 China Yunnan Power Grid Co. Ltd. Kunming650011 China Research Institute of China Southern Power Grid Beijing102209 China

ISBN: (纸本)9798350368604

With the increasing penetration of new energy sources such as wind and solar, accurate source-side power forecasting helps power system dispatchers to obtain new energy pre-output plans and improve the power system's new energy consumption capacity through the coordination of multiple power generation resources. The wind and photovoltaic power data are characterized by large fluctuations, strong nonlinearity, instability, and strong time dependence, etc. Through "Decomposition-Prediction", the original sequence is decomposed into a number of sub-sequences, which reduces the volatility and randomness of the original sequence, and has been widely used in wind and photovoltaic power prediction. In order to solve the problem that traditional decomposition algorithms have insufficient decomposition capability to extract data features in a targeted and effective way, we propose a wind and photovoltaic power prediction method based on Feature Mode Decomposition and Cooperative Learning Strategy: the CoFMD-BiLSTM model. A novel emerging decomposition algorithm, Feature Mode Decomposition (FMD), originally applied in fault detection, is introduced. By designing a Cooperative Learning Strategy to learn and fit the decomposition sequence information obtained from the FMD decomposition covering different features, which is fed into the BiLSTM model to obtain the wind and light power predictions. The actual operation data of Sotavento Galicia (sg) wind farm in Spain and TuoZhuo photovoltaic farm in Yunnan, china are used. Compared with the two models, VMD-BiLSTM and BiLSTM, the validation results show that the wind and solar power prediction method based on the CoFMD-BiLSTM model can effectively improve the accuracy of wind and solar power prediction. © 2024 IEEE.

关键词： BiLSTM Cooperative Learning Strategy FMD Wind and Photovoltaic power forecasting

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7th International Conference on High Performance Compilation, Computing and Communications, HP3C 2023

作者： Liu, Xingyang Wang, Xi Kou, Lei Wang, Jian Gao, Shibin Zhang, Benfa Yu, Long Ke, Wende School of Electrical Engineering Southwest Jiaotong University China Nanchong Power Supply Company State Grid Sichuan Electric Power Corporation China China State Grid Songyuan Power Supply Company State Grid Jilin Electric Power Corporation China Department of Mechanical and Energy Engineering Southern University of Science and Technology China

ISBN: (纸本)9781450399883

Due to highly complicated working conditions of overhead contact lines, it is inevitable to suffer from the dynamic external weather conditions and environmental factors, and further trigger a variety of risk events, even causing a series of serious consequences. To prevent the weather-related risks in advance, this paper proposes a weather-related failure risk prediction approach based on deep gaussian process (DGP), with its superior performance of nonlinear processing and uncertainty quantification. After preprocessing the weather data and the associated failure records, the weather-related failure risk prediction dataset is established for the studied issue of this paper, that is predictive classification problem. To simultaneously predict the lighting-related trip-out, wind-related floater intrusion, and fog-haze-related pollution flashover risk, a multi-task learning framework in DGP is formulated to capture the complex dependencies between weather parameters and OCL failure risk. The extensive experiments investigated on the constructed dataset reflect the effectiveness and superior of the proposed approach, with capacity of uncertainty quantification and giving trustworthy prediction results. © 2023 ACM.

关键词： Deep learning

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Stochastic Multi-Objective Optimal Dispatching Method for Improving Wind power Accommodation Ability 16

Stochastic Multi-Objective Optimal Dispatching Method for Im...

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16th IEEE PES Asia-Pacific power and Energy Engineering Conference, APPEEC 2024

作者： Diao, Haoran Zhai, Hefeng Qi, Ang Zhang, Yumin Zhang, Nianshang China Southern Power Grid Co. Ltd. Guangzhou China Electric Power Research Institute Csg Key Laboratory of Hvdc Guangzhou China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9798350386127

With the ever-increasing penetration of renewable energy sources (RESs), like solar and wind, the randomness and intermittency of RESs have imposed significant obstacles on the operation of electricity systems. To hedge against the uncertainty stemming from RESs, a host of inspiring stochastic programming (SP) based approaches are introduced. In this context, we present a random multi-objective dispatching method for wind power accommodation, aiming to address the wind curtailment issue in single-objective SP-based frameworks. The first objective is to reduce the unit operating and load shedding costs, while the second objective is to optimize the wind power accommodation capacity. Then, the preemptive programming goal technique is leveraged to handle the proposed multi-objective optimization model. The efficiency of the suggested strategy is assessed on the IEEE 14-bus and 118-bus test systems. © 2024 IEEE.

关键词： Windmill

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A CVT Parameter Identification Method Based on Improved Grey Wolf Optimizer 2

A CVT Parameter Identification Method Based on Improved Grey...

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2nd International Conference on Frontiers of Electrical power and Energy Systems, EPES 2022

作者： Yu, Yuchen Chen, Xuxuan Tang, Hao Lei, Yuanyuan College of Information Science and Engineering Wuhan University of Science and Technology Hubei Wuhan430081 China China Southern Power Grid Research Institute Guangdong Guangzhou510663 China

Aiming at the problem that harmonic simulation model parameters of capacitive voltage transformer (CVT) are difficult to determine, an identification method of equivalent circuit parameters of CVT is proposed. By studying the frequency response, a nonlinear equation about the equivalent circuit parameters of CVT is established. By analyzing the characteristics of the equation and combining with the actual use, an improved grey wolf optimizer is applied to achieve the accurate identification of the key parameters of CVT. On the basis of grey wolf optimizer, the algorithm introduced a good point set and comprehensive dimension learning strategy to prevent the algorithm from falling into local optimum, and modified the convergence factor according to the actual needs to improve the convergence accuracy. Finally, three numerical examples are simulated by MATLAB/Simulink software, which proves the feasibility and superiority of the proposed method in CVT application. © Published under licence by IOP Publishing Ltd.

关键词： Nonlinear equations

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Moisture Absorbing Properties of Alkylbenzenes with Experiment and Molecular Dynamics Simulation Calculation 6

Moisture Absorbing Properties of Alkylbenzenes with Experime...

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2024 6th International Conference on Advanced Materials and Ecological Environment, AMEE 2024

作者： Liu, Zhifeng Zhou, Shangming Liao, Jianping Gao, Fan Chen, Yufei Zhu, Zhiping Electric Power Research Institute of EHV Transmission Company China Southern Power Grid Co. Ltd. Guangdong Guangzhou510405 China School of Chemistry and Chemical Engineering Changsha University of Science and Technology Hunan Changsha410114 China

The presence of moisture accelerates the aging of insulating oil thus greatly reducing the insulating performance. In this study, in order to investigate their absorb moisture characteristics, comparison experiments and molecular dynamics simulation calculations at 1wt% oil-water mixing were carried out for the alkylbenzene insulating oil, mineral oil and vegetable oil. The experiment results show that vegetable oil has the strongest moisture absorption ability, alkylbenzene insulating oil is the second, and mineral oil is the weakest at temperature 15-45°C and relative humidity 90%, as the temperature rises from 15°C to 30°C, the growth of the moisture absorption rate is significant, but as temperature rises from 30°C to 45°C the increase tendency is smaller;the results of molecular dynamics simulation the show that with the increase of temperature, the molecular motion is intensified, the interaction energy decreases, and the free volume and diffusion coefficient increase. These results help to understand the moisture absorption mechanism of alkylbenzene insulating oil and provide a theoretical basis for its storage and use. © Published under licence by IOP Publishing Ltd.

关键词： Sustainable development

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Improved harris corner point algorithm for anti-vibration hammer line clip gap detection 3

Improved harris corner point algorithm for anti-vibration ha...

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3rd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2023

作者： Zhong, Liqiang Lei, Ting Wu, Wenjie China Southern Power Grid Technology Co. Ltd. Guangzhou China College of Electricity and Information Engineering Changsha University of Science & Technology Changsha410114 China

ISBN: (纸本)9781510668522

To address the current problems of low accuracy and poor precision of anti-vibration hammer line clip gap detection, the thesis proposes an improved Harris corner point algorithm for anti-vibration hammer line clip gap detection. Firstly, the DeepLabV3+ semantic segmentation algorithm is used to pre-process the anti-vibration hammer images, and the traditional Harris algorithm is used to obtain the pixel-level corner points as the central corner points, which are continuously approximated by the least squares iterative calculation, and finally the sub-pixel-level corner point coordinates are calculated to greatly improve the accuracy of gap detection. Finally, an adaptive thresholding algorithm is used to find the best threshold value for each image, which improves the accuracy of detection. The experimental results show that the average offset of coordinates using the improved Harris corner point detection algorithm is 0.2 pixels, which is 0.6 pixels lower than the average offset of the Harris corner point detection algorithm and greatly improves the detection accuracy. Hariis corner point detection using the adaptive thresholding algorithm can greatly reduce the number of pseudo corner points and improve the accuracy of detection compared to the traditional manual adjustment of the threshold. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Hammers

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Analytical Model and Topology Optimization of Doubly-fed Induction Generator

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CES Transactions on Electrical Machines and Systems 2024年第2期8卷 162-169页

作者： Lu Sun Haoyu Kang Jin Wang Zequan Li Jianjun Liu Yiming Ma Libing Zhou the State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074China IEEE Dongfang Electric Machinery Co. LtdDongfang Electric CorporationDeyangChina CSG PGC Energy Storage Research Institute Southern Power Grid Energy Storage Co.LtdGuangzhou 510630China

As the core component of energy conversion for large wind turbines,the output performance of doubly-fed induction generators (DFIGs) plays a decisive role in the power quality of wind *** realize the fast and accurate design optimization of DFIGs,this paper proposes a novel hybriddriven surrogate-assisted optimization *** firstly establishes an accurate subdomain model of DFIGs to analytically predict performance ***,taking the inexpensive analytical dataset produced by the subdomain model as the source domain and the expensive finite element analysis dataset as the target domain,a high-precision surrogate model is trained in a transfer learning way and used for the subsequent multi-objective optimization *** on this model,taking the total harmonic distortion of electromotive force,cogging torque,and iron loss as objectives,and the slot and inner/outer diameters as parameters for optimizing the topology,achieve a rapid and accurate electromagnetic design for ***,experiments are carried out on a 3MW DFIG to validate the effectiveness of the proposed method.

关键词： Doubly-fed induction generators Accurate subdomain model Surrogate-assisted Transfer learning

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