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Accelerating exploitation and integration of global renewable energy

Innovation 2025年

作者： Wang, Jianxiao Chen, Xinjiang Zhuang, Minghao Li, Yan Ruan, Ziwen Wang, Yuhan Zhang, Ning Song, Jie He, Kebin Lu, Xi National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing100871 China Department of Industrial Engineering and Management College of Engineering Peking University Beijing100871 China Peking University Ordos Research Institute of Energy Ordos017000 China State Key Laboratory of Nutrient Use and Management College of Resources and Environmental Sciences China Agricultural University Beijing100193 China College of Environmental Science and Engineering Tongji University Shanghai200092 China School of Environment State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua University Beijing100084 China State Key Lab of Power Systems Department of Electrical Engineering Tsinghua University Beijing100084 China Institute for Carbon Neutrality Tsinghua University Beijing100084 China

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Machine condition classification using deterioration feature extraction and anomaly determination

Machine condition classification using deterioration feature...

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作者： Jiang, Dongxiang Liu, Chao State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Thermal Engineering Tsinghua University Beijing 100084 China

Condition classification has been widely used for assessing equipment status for machine condition monitoring and diagnostics. An engine was fitted with one temperature and two pressure sensors to study the machine conditions in prognostics with an added abnormal state, in addition to the conventional normal and failure states. This work enables a better classification capability in order to predict deterioration in the engine. Information related to three deterioration processes was collected, and preprocessed using singular point elimination, deviation value acquisition, and data normalization. Wavelet transforms were used to extract deterioration features with different mother wavelets. The mother wavelets were selected using t tests to optimize the wavelet selection. The deterioration was related to the amount of anomaly, with the abnormal states defined to distinguish the functional from the failure states. A Learning Vector Quantization (LVQ) neural network was used to classify the machine conditions, including normal, abnormal, and failure states. The results showed that the deterioration features defined using the Daubechies wavelet (db8) most strongly correlated with the original signal, so that the classification accuracy based on the deterioration features was greatly improved. The LVQ classification system had good accuracy for machine condition classification, and was adaptable to various engine conditions. © 2010 IEEE.

关键词： Deterioration

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Series-connected HV-IGBTs using active voltage control with status feedback circuit

Series-connected HV-IGBTs using active voltage control with ...

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作者： Ji, Shiqi Lu, Ting Zhao, Zhengming Yu, Hualong Yuan, Liqiang State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China

ISBN: (纸本)9781479956982

The transient voltage unbalance is the major problem that limits the application of series-connected IGBTs in high voltage and high power converters. The asynchronous gate delay which causes that series-connected IGBTs do not turn-on and turn-off at the same time results in the most serious unbalanced voltage sharing. The active voltage control technique is proposed in this paper to solve the asynchronous gate delay problem. By sampling the feedback signal caused by unbalanced voltage, the microcontroller generates a time delay for gate driver to compensate the asynchronous gate delay. The most vital part of active voltage control is the status feedback circuit which is also given in detail in this paper. The function of the status feedback circuit and the effect of active voltage control are verified in a two series-connected HV-IGBTs platform in rated operation (5kV bus voltage and 600A load current). © 2014 IEEE.

关键词： Insulated gate bipolar transistors (IGBT)

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Optimal Sizing of Photovoltaic and Battery Energy Storage of Electric Vehicle Charging Station Based on Two-part Electricity Pricing

Optimal Sizing of Photovoltaic and Battery Energy Storage of...

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2020 IEEE Sustainable power and Energy Conference, iSPEC 2020

作者： Wang, Conghui Tian, Liting Zhang, Fang Cheng, Lin School of Electrical Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Tsinghua University Beijing China

ISBN: (纸本)9781728191645

This paper focuses on optimal sizing of photovoltaic (PV) and battery energy storage system (BESS) of special-use charging station for electric taxi cabs. Aiming to minimize annual equivalent cost of the charging station under two-part electricity pricing mechanism, an optimal sizing algorithm of PV and BESS is established considering the randomness of PV output and the power constraint of the grid, as well as whether charging station participates in demand response (DR). The cooperative operation strategies of charging facilities, PV and BESS under typical scenarios are proposed. Considering the factors that affect the optimal results, this paper provides sensitivity analysis in a charging station. Finally, the proposed optimal sizing algorithm is verified in the charging station equipped with 24 EV charging piles, and the economic analysis of the optimal sizing scheme is carried out. Based on economical analysis of optimal sizing results, it is found out that the equivalent cost of EV charging station is lower when participating in demand response. The results show that the annual equivalent total cost of the charging station is significantly reduced under the new optimal sizing scheme. © 2020 IEEE.

关键词： Sensitivity analysis

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Application of fuzzy-rough set theory and improved SMO algorithm in aircraft engine vibration fault diagnosis

Application of fuzzy-rough set theory and improved SMO algor...

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2012 3rd Annual IEEE Prognostics and System Health Management Conference, PHM-2012

作者： Xu, Hongzhi Jiang, Dongxiang Liang, Lei State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Thermal Engineering Tsinghua University Beijing 100084 China

Aircraft engine is an important component of the airplane, which lifespan and reliability have directly influence to flight safety. Vibration analysis is an effective fault diagnosis method for airplane's mechanical construction fault. Several typical vibration faults have drawn from the vibration analysis on the basis of fault mechanism in aircraft engine, and the standard vibration fault-symptom (Fuzzy Membership) relationship table have constructed based on Fuzzy Mathematic theory in this paper. Sample data are simulated on the basis of this table. Sequential Minimal Optimization (SMO) is a fast algorithm for training Support Vector Machines (SVM). The simulated result showed a great improvement on computation efficiency by selecting double threshold parameter for SMO algorithm than single threshold. In order to examine the algorithm's effect applying in the aircraft engine fault diagnosis, Radial Basis Function (RBF) Neural Network, C4.5 Decision Tree, SVM (chunking), Platt's SMO and Improved SMO algorithm are applied to the training data and test data. It is shown that the Improved SMO algorithm displayed superior comprehensive performance. Finally, the vibration fault feature is reduced based on Fuzzy-Rough Sets theory. The research shows that the Improved SMO algorithm is quicker than other algorithm in aircraft engine fault diagnosis with the reduced feature attributes, and its accuracy is high. © 2012 IEEE.

关键词： Support vector machines

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Optimal Allocation Strategy of Frequency Modulation power for Multiple Energy Storage systems Considering Dual Constraints of Frequency Modulation Cost and Frequency Modulation Capability

Optimal Allocation Strategy of Frequency Modulation Power fo...

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2023 IEEE International Conference on power Science and Technology, ICPST 2023

作者： Peng, Yongming Si, Wenbo Zhao, Haiji Lv, Changlin Liu, Chengzhe Xu, Fei Hao, Ling Li, Junhui Northeast Branch of State Grid Corporation of China Shenyang China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin China State Key Laboratory of Power System and Power Generation Equipment Control and Simulation Beijing China

ISBN: (纸本)9798350311358

Aiming at the power allocation problem of multiple energy storage power stations distributed at different locations in the regional power grid participating in frequency modulation services, a frequency modulation power optimization allocation strategy for multiple energy storage systems considering the dual constraints of frequency modulation cost and frequency modulation capability is proposed. Firstly, a multi-objective optimization allocation model for frequency modulation power is constructed with the minimum frequency modulation cost and minimum deviation of the state of charge (SOC) for energy storage power plants. Secondly, using Pareto based multi-objective genetic algorithm (MOGA) to solve the model, introduce adaptive weight coefficients and fuzzy membership functions for each objective function regarding the frequency regulation demand of the power grid and the deviation of the SOC of energy storage stations, construct a comprehensive satisfaction function to make decisions on the most advantageous points on the Pareto frontier, in order to obtain the optimal output of each energy storage station that can adapt to the frequency regulation requirements of the power grid. Finally, simulation analysis was conducted on the proposed strategy in this article, and the results showed that: The proposed strategy not only enhances the frequency regulation economy of the regional power grid, but also helps to restore the SOC of the energy storage power station. © 2023 IEEE.

关键词： Frequency modulation

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Misalignment fault detection in dual-rotor system based on time frequency techniques

Misalignment fault detection in dual-rotor system based on t...

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Society for Machinery Failure Prevention Technology Annual Conference 2017: 50 Years of Failure Prevention Technology Innovation, MFPT 2017

作者： Wang, Nan-Fei Jiang, Dong-Xiang Han, Te State Key Laboratory of Control Simulation of Power System and Generation Equipment Department of Thermal Engineering Tsinghua University Beijing100084 China

In order to improve the energy efficiency and compact structure, the dual-rotor structure including lowpressure rotor and high-pressure rotor has been widely used in aero-engine. Misalignment is one of the most common faults in dual-rotor system, which will causes malfunctions. It is a significant task for rotor dynamics personnel to monitor and defect faults in dual-rotor system. In the paper, the dual-rotor vibration signals are applied to solve the fault identification problem by utilizing time frequency techniques. Numerical simulations are carried out through finite element analysis of dual-rotor system with misalignment fault. Two signal processing tools namely Short Time Fourier Transform (STFT) and Continuous Wavelet Transform are used to detect the misalignment fault and compared to evaluate their diagnosis performance. The effect of addition of Signal to Noise (SNR) on three frequency techniques is presented. Experiments are carried out to obtain the vibration data of dual-rotor test rig and the results from the work show that the technique can be used for the monitoring of misalignment, which will have applications in the condition monitoring and maintenance of various types of rotating machinery.

关键词： Condition monitoring

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Inspection Text Classification of power equipment Based on TextCNN 16th

Inspection Text Classification of Power Equipment Based on T...

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16th Annual Conference of China Electrotechnical Society, ACCES 2021

作者： Chen, Jianning Zhou, Yuanxiang Ge, Jiamin State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China

ISBN: (纸本)9789811918698

A large number of text and reports about the power equipment are generated in power system, which consist of implicit information of operation condition and insulation status. With the development of convolutional neural network (CNN), the inspection text can be analyzed intelligently to improve the reliability of power system. In order to extract valuable information from inspection text for state evaluation of power equipment in local area, an information extraction model for inspection text based on TextCNN is proposed, improved and verified. First, the feature embedding of inspection text were performed by Word2Vec method. Secondly, the corpus were augmented with back translation method. Then, the TextCNN was adopted to classify the risk level of the power equipment or area involved in the inspection text. Finally, the classification results from the model were evaluated by classification accuracy, F1 score, confusion matrix and compared with the model based on BiLSTM and RCNN. The results demonstrated that the performance of TextCNN was the best among the three models on augmented dataset by back translation method with ACC and F1 scores of 0.9087 and 0.9099, respectively, which is the most suitable model among these three for recognition and classification of inspection text of power equipment. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Inspection

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Analysis of Application of Superconducting Fault Current Limiter to AC Line of HVDC 8

Analysis of Application of Superconducting Fault Current Lim...

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8th IEEE International Conference on Advanced power System Automation and Protection, APAP 2019

作者： Chen, Binshu Dong, Xinzhou Tsinghua University Key Lab of Control and Simulation of Power Systems and Generation Equipment Dept. of Electrical Engineering China

ISBN: (纸本)9781728117225

In LCC-HVDC hybrid grid, commutation failure is an important factor affecting system stability. When there is a fault or a large voltage fluctuation in AC line of LCC-HVDC, a commutation failure will occur. Fault current limiter (FCL) can limit the fault current and prevent commutation failure. Superconducting current limiters using superconducting materials as the core component, have no power loss and do not affect the dynamic performance of the system during normal operation. This article analyze how SFCL acts to suppress commutation failure in AC/DC hybrid systems, and describes the various types of SCFCLs and their limitations for this scene. By building simulation models of SCFCLs applied to AC line of LCC-HVDC invert, the author analyzes the effect of SCFCL on the hybrid grid. © 2019 IEEE.

关键词： Superconducting fault current limiters

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Evaluation Method of Wind power Consumption Limitation in power System with High Proportion of Wind power 4

Evaluation Method of Wind Power Consumption Limitation in Po...

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4th IEEE China International Electrical and Energy Conference, CIEEC 2021

作者： Wang, Hongye He, Li Lin, Xuelong Ma, Jing An, Baihui Yang, Weixiang Xu, Fei Hou, Tao Li, Jing Feng, Changsheng Li, Junhui Co. Ltd Beijing China State Key Lab of Control and Simulation of Power Systems and Generation Equipment Tsinghua University Beijing China

ISBN: (纸本)9781728171494

In order to study the reasonable capacity of power grid to absorb wind power, a new calculation method is proposed for the combined system of thermal power and wind power. In this paper, the probability and statistics method is used to analyze the output characteristics of wind farm, and the influence of characteristic index on wind farm is studied. A new calculation method of wind power limit is proposed, and the influence of seasonal factors is introduced to study the situation of wind power limit in summer and winter. Through the actual example, the idea and method are provided to formulate the control principle of wind power output, and the rationality and effectiveness of the proposed method are verified. © 2021 IEEE.

关键词： Electric power utilization

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