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A Multi-Model Fusion Approach for Transformer Fault Detection

A Multi-Model Fusion Approach for Transformer Fault Detectio...

Information Technology,Big Data and Artificial Intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Ke Zhou Wei Zhang Ligang Li Shaoming Pan Chengwei Huang Guangxi Power Grid Equipment Monitoring and Diagnosis Technology Innovation Center Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Electric Power Research Institute of Guangxi Power Grid CO. LTD. Nanning State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences China Power Supply Bureau of Guangxi Hezhou Power Grid Co. Ltd.

ISBN: (数字)9798350363609

ISBN: (纸本)9798350363616

Addressing the weak generalization capability and suboptimal prediction performance of single mechanistic and data-driven models, this paper proposes a transformer fault detection method based on the fusion of mechanism and data models. Firstly, vibration and current data are collected on-site to train the SVM vibration model and the Adaboost current model. Secondly, current simulation data is obtained using laboratory simulation software. This simulation data, combined with the current data collected under the same conditions on-site, is used as input to train the GBDT error compensation model. Finally, these three models are used as inputs to the GRNN, completing the overall model design. This fusion of mechanistic and data-driven models not only addresses the parameter mismatch issue of the mechanistic model under complex working conditions but also deeply mines time-series data. Experimental results show that The mean squared error of the fusion model is 0.002 lower than that of the data model, and the coefficient of determination is improved by 5.07% compared to the mechanistic model, enhancing the overall predictive accuracy of the model.

关键词： Vibrations Support vector machines Training Accuracy Biological system modeling Fault detection Predictive models Transformers Prediction algorithms Data models

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Chance-Constrained Generic Energy Storage Operations under Decision-Dependent Uncertainty

arXiv

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arXiv 2022年

作者： Qi, Ning Pinson, Pierre Almassalkhi, Mads R. Cheng, Lin Zhuang, Yingrui State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China The Dyson School of Design Engineering Imperial College London LondonSW7 2AZ United Kingdom The Department of Electrical and Biomedical Engineering University of Vermont BurlingtonVT05405 United States

Compared with large-scale physical batteries, aggregated and coordinated generic energy storage (GES) resources provide low-cost, but uncertain, flexibility for power grid operations. While GES can be characterized by different types of uncertainty, the literature mostly focuses on decision-independent uncertainties (DIUs), such as exogenous stochastic disturbances caused by weather conditions. Instead, this manuscript focuses on newly-introduced decision-dependent uncertainties (DDUs) and considers an optimal GES dispatch that accounts for uncertain available state-of-charge (SoC) bounds that are affected by incentive signals and discomfort levels. To incorporate DDUs, we present a novel chance-constrained optimization (CCO) approach for the day-ahead economic dispatch of GES units. Two tractable methods are presented to solve the proposed CCO problem with DDUs: (i) a robust reformulation for general but incomplete distributions of DDUs, and (ii) an iterative algorithm for specific and known distributions of DDUs. Furthermore, reliability indices are introduced to verify the applicability of the proposed approach with respect to the reliability of the response of GES units. simulation-based analysis shows that the proposed methods yield conservative, but credible, GES dispatch strategies and reduced penalty cost by incorporating DDUs in the constraints and leveraging data-driven parameter identification. This results in improved availability and performance of coordinated GES units. © 2022, CC BY.

关键词： Energy storage

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Functionality identification for the testing systems with large-scale highly-concentrated wind power integration by long-distance transmission lines

Functionality identification for the testing systems with la...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Jiabing Hu Yunhe Hou Feng Liu Yongning Chi Shuanglei Feng Haiyan Tang Guobing Song Xiaoming Yuan State Key Lab of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan China Department of Electrical and Electronic Engineerig The University of Hong Kong Hong Kong China State Key Lab of Control and Simulation of Power Systems and Generation Equipment Tsinghua University Beijing China China Electric Power Research Institute Beijinz China Department of Electrical Engineering Xi’ an Jiaotong University Xi'an China

ISBN: (纸本)9781479977215

Large-scale, highly-concentrated wind power integrated into grids through long transmission lines will bring significant challenges to power system operation during steady-state and dynamic processes. Tremendous research has been conducted in this critical area. However, few, if any available testing systems have been established to meet the requirements of the research on different time-scales. The objective of this paper is to identify the functionality requirements of the testing systems for the comprehensive studies, which covers different time-scale problems of power systems. For this purpose, the realistic Gansu power grids in China and wind farms in Jiuquan area are selected. As a typical power grid with large-scale highly-concentrated wind power integration by long-distance transmissions, the characteristics of the selected wind farms and power grid are discussed first. Two simplified systems are constructed associated with the major characteristics. The critical functionality requirements of the testing systems for different research purposes, i.e., system planning, operation, control, and protection, are identified. As the first step, this paper scopes the key requirements and, ultimately, a complete testing system is expected.

关键词： Wind power generation power system stability Stability analysis Testing Wind farms Frequency control power grids

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Research on Digital Twin Modeling Method for Combustion Process Based on Model Reduction

SSRN

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SSRN 2024年

作者： Zhang, Yue Li, Jiale Department of Automation North China Electric Power University Hebei Baoding071000 China Hebei Technology Innovation Center of Simulation & Optimized Control for Power Generation North China Electric Power University China Baoding Key Laboratory of State Detection and Optimization Regulation for Integrated Energy System China

In response to the difficulty in obtaining combustion information within coal-fired boiler furnaces, a method is proposed in this study to improve the reduced-order model using clustering segmentation. This approach aims to rapidly predict the combustion temperature field inside the furnace by establishing a twin model of the combustion temperature field. Initially, a finite element method is employed to analyze the combustion system of a 600MW subcritical boiler under various operating conditions. Subsequently, cross-sectional data from burner nozzle positions at each operating condition are extracted. These data are subjected to Proper Orthogonal Decomposition (POD), Spectral Proper Orthogonal Decomposition (SPOD), and Wavelet Transform-POD (WT-POD) for dimensionality reduction to obtain modal data. Comparative analyses are conducted on the modal data obtained from different methods. Furthermore, based on modal data analysis, a Support Vector Machine (SVM) regression model is selected to reconstruct the temperature field. The average absolute error of the reconstructed temperature fields from three methods under different operating conditions is then compared. Finally, the model is refined using clustering segmentation, resulting in an improvement of approximately 0.6% in reconstruction accuracy. This enhancement demonstrates that the clustered POD-SVR-GA model achieves higher accuracy in reconstructing combustion temperature fields after clustering-based improvements. © 2024, The Authors. All rights reserved.

关键词： Support vector machines

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Study on regional hydropower accommodation and improvement measures in power system

Study on regional hydropower accommodation and improvement m...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Zewen Li Zhaohong Bie Zifen Han Xiaofei Li Yong Zhi Yankai Zhang The State Key Laboratory of Electrical Insulation and Power Equipment Xi'an Jiaotong University Xi'an China State Grid Gansu Electric Power Company Lanzhou China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing China Electric Power Research Institute State Grid Gansu Electric Power Company Lanzhou China

ISBN: (纸本)9781538614280

Hydropower is an important part of energy internet, as a principal type of sustainable energy. The promotion of hydropower may help to improve the power source structure and improves the safety, reliability and flexibility of the power system. However, the increasing congestion of the regional hydropower accommodation limits the wider use of hydropower. In this paper, an index system is developed to assess the regional hydropower accommodation. On this basis, an analysis method is proposed to find out the specific reasons of the congestion and the improvement measures by analyzing the relevance of source-load characters and delivery flowgate. The method is proved to be universal and practical through a case study in Western China where the hydropower is the dominant energy. The study is capable to provide necessary suggestions to the safety operation and planning of regional power system and has engineering application value.

关键词： Hydroelectric power generation power systems Indexes Floods power measurement Pollution measurement Planning

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Performance Analysis on Hydrogen-Battery Coordination Storage for Renewable Energy Accommodation in Large-Scale power System

Performance Analysis on Hydrogen-Battery Coordination Storag...

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Smart power & Internet Energy systems (SPIES), International Conference on

作者： Xiaopan Chen Qi Yang Na Meng Yan Cheng Jiang Wu Guanchu Chen MOEKLINNS Xi’an Jiaotong University Xi’an China Xinjiang Key Laboratory of Whole Process Simulation for Power System Electric Power Research Institute of State Grid Xinjiang Electric Power Co. Ltd. Urumqi China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing China

Energy storage is an effective measure to address the renewable energy curtailment problem in large-scale power systems. However, installing the same type of energy storage has limited improvement to the entire system when the total installed capacity of energy storage is fixed. In this paper, an optimal scheduling method for the hydrogen-battery coordination storage system is proposed to further improve renewable energy accommodation by combining the advantages of different types of energy storage. The coupling relationship between the power grid and the heat grid is also considered a way to reduce energy waste. Case tests based on actual operating data analyze the performance of systems with different energy storage configurations. Results indicate the effectiveness of the proposed method. The optimal installed capacity for hydrogen energy storage and battery energy storage is further researched to provide advice for energy storage planning.

关键词： Couplings Renewable energy sources Hydrogen storage Hydrogen Optimal scheduling power grids Planning

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Traveling waves based faulted feeder selector and its field application

Traveling waves based faulted feeder selector and its field ...

引用

International Conference on Advanced power System Automation and Protection (APAP)

作者： Shenxing Shi Jun Wang Aiming Li Xinchun Du Xiaoxia Cao Yajun Du Xinzhou Dong State Key Lab of Control and Simulation of Power Systems and Generation Equipments Dept. of Electrical Engineering Tsinghua University Haidian District Beijing 100084 China Yulin power company Shaanxi 719000 China China Jiuquan Satellite Launch Center Plumbing Electrical Station 732750 China

The paper proposes faulted feeder selector in power distribution system with neutral non-effectively grounded. At first, the paper presents basic principle of single-phase-to-ground fault feeder selection based on traveling waves, which compares amplitude and polarity of the initial current traveling waves in all feeders. Then the implementation scheme, including hardware design and software flowchart is presented. At last field application of faulted feeder selector is introduced. The field operation results validated the correctness of faulted feeder selector based on transient traveling wave.

关键词： Circuit faults Random access memory Transient analysis power distribution Automation

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Risk-based study on under voltage load shedding schemes

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Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering 2006年第19期26卷 18-22页

作者： Dai, Jian-Feng Zhu, Ling-Zhi Zhou, Shuang-Xi Lu, Zong-Xiang State Key Lab. of Control and Simulation of Power Systems and Generation Equipments Dept. of Electrical Engineering Tsinghua University Beijing 100084 China

A risk based method is proposed to design under voltage load shedding (UVLS) scheme. Different with traditional methods, the proposed one employs a series of risk indices, which are obtained based on a full-scale contingencies analysis, to determine the operating parameters of load shedding. According to this method, the load bus, in which the UVLS can exert itself with the highest efficiency to prevent voltage collapse, is selected as the first candidate to execute load shedding. And the amount of loads to be shed is identified though a relationship between risk values and shedding amount. The selection of shedding time conforms to the principle that the compound risk brought by failed shedding and unexpected shedding must be the minimum. Experiments conducted for IEEE 39-bus system reveal that the proposed method redound to identify the location, amount and time of load shedding more accurately and reasonably due to taking into account a great deal of uncertain factors.

关键词： Electric load shedding

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Design of the PID temperature controller for an alkaline electrolysis system with time delays

arXiv

引用

arXiv 2022年

作者： Qi, Ruomei Li, Jiarong Lin, Jin Song, Yonghua Wang, Jiepeng Cui, Qiangqiang Qiu, Yiwei Tang, Ming Wang, Jian State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing China Tsinghua-Sichuan Energy Internet Research Institute Chengdu China Department of Electrical and Computer Engineering University of Macau China School of Materials Science and Engineering Shanghai University Shanghai China Purification Equipment Research Institute of CSIC Handan China College of Electrical Engineering Sichuan University Chengdu China

Electrolysis systems use proportional-integral-derivative (PID) temperature controllers to maintain stack temperatures around set points. However, heat transfer delays in electrolysis systems cause manual tuning of PID temperature controllers to be time-consuming, and temperature oscillations often occur. This paper focuses on the design of the PID temperature controller for an alkaline electrolysis system to achieve fast and stable temperature control. A thermal dynamic model of an electrolysis system is established in the frequency-domain for controller designs. Based on this model, the temperature stability is analysed by the root distribution, and the PID parameters are optimized considering both the temperature overshoot and the settling time. The performance of the optimal PID controllers is verified through experiments. Furthermore, the simulation results show that the before-stack temperature should be used as the feedback variable for small lab-scale systems to suppress stack temperature fluctuations, and the after-stack temperature should be used for larger systems to improve the economy. This study is helpful in ensuring the temperature stability and control of electrolysis systems. Copyright © 2022, The Authors. All rights reserved.

关键词： Three term control systems

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Fault diagnosis for PV arrays considering dust impact based on transformed graphical feature of characteristic curves and convolutional neural network with CBAM modules

arXiv

引用

arXiv 2023年

作者： Qu, Jiaqi Wei, Lu Sun, Qiang Zareipour, Hamidreza Qian, Zheng School of Instrumentation and Optoelectronic Engineering Beihang University Beijing China School of Electronics and Information Engineering Beihang University Beijing China State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing China The Department of Electrical and Computer Engineering University of Calgary Calgary Canada

Various faults can occur during the operation of PV arrays, and both the dust-affected operating conditions and various diode configurations make the faults more complicated. However, current methods for fault diagnosis based on I-V characteristic curves only utilize partial feature information and often rely on calibrating the field characteristic curves to standard test conditions (STC). It is difficult to apply it in practice and to accurately identify multiple complex faults with similarities in different blocking diodes configurations of PV arrays under the influence of dust. Therefore, a novel fault diagnosis method for PV arrays considering dust impact is proposed. In the preprocessing stage, the Isc-Voc normalized Gramian angular difference field (GADF) method is presented, which normalizes and transforms the resampled PV array characteristic curves from the field including I-V and P-V to obtain the transformed graphical feature matrices. Then, in the fault diagnosis stage, the model of convolutional neural network (CNN) with convolutional block attention modules (CBAM) is designed to extract fault differentiation information from the transformed graphical matrices containing full feature information and to classify faults. And different graphical feature transformation methods are compared through simulation cases, and different CNN-based classification methods are also analyzed. The results indicate that the developed method for PV arrays with different blocking diodes configurations under various operating conditions has high fault diagnosis accuracy and reliability. Copyright © 2023, The Authors. All rights reserved.

关键词： Failure analysis

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