587 research outputs found
Wavelet Transform Based Methods for Fault Detection and Diagnosis of HVDC Transmission Systems
No full textABSTRACT WAVELET TRANSFORM BASED METHODS FOR FAULT DETECTION AND DIAGNOSIS OF HVDC TRANSMISSION SYSTEMS by Zhonxguan Li The University of Wisconsin-Milwaukee, 2019 Under the Supervision of Professor Lingfeng Wang High-voltage direct current (HVDC) is a key enabler in power system. HVDC offers a most efficient means of transmitting large amount of power. Applications of HVDC can improve the operation security, reliability performance and economy of power systems. Due to factors inside and outside the HVDC system, the system will experience various faults, which have infected HVDC system. VSC-HVDC is a HVDC transmission based on IGBT and PWM. VSC-HVDC direct current transmission has broad application prospects in new energy grid-connected and grid-connected transformation. In this research, aiming at the fault diagnosis of VSC-HVDC, the fault diagnosis and fault detection are studied. In this research, a VSC-HVDC was simulated in MATLAB Simulink, and an adjusted VSC-HVDC model was built. The models were applied to simulate the basic operation of VSC-HVDC and main faults on AC and DC side in the VSC-HVDC system. Take line current on AC or DC side as input data, the result data after wavelet processing was applied in HVDC faults diagnosis. To verify the function of fault detection, DC faults at different locations were set in the adjusted model. Wavelet entropy was applied in fault diagnosis and detection to gather accurate results. According to the simulation results, wavelet transform exhibits a good performance in HVDC fault diagnosis and detection.2020-06-0
Wavelet Transform Based Methods for Fault Detection and Diagnosis of HVDC Transmission Systems
No full textABSTRACT WAVELET TRANSFORM BASED METHODS FOR FAULT DETECTION AND DIAGNOSIS OF HVDC TRANSMISSION SYSTEMS by Zhonxguan Li The University of Wisconsin-Milwaukee, 2019 Under the Supervision of Professor Lingfeng Wang High-voltage direct current (HVDC) is a key enabler in power system. HVDC offers a most efficient means of transmitting large amount of power. Applications of HVDC can improve the operation security, reliability performance and economy of power systems. Due to factors inside and outside the HVDC system, the system will experience various faults, which have infected HVDC system. VSC-HVDC is a HVDC transmission based on IGBT and PWM. VSC-HVDC direct current transmission has broad application prospects in new energy grid-connected and grid-connected transformation. In this research, aiming at the fault diagnosis of VSC-HVDC, the fault diagnosis and fault detection are studied. In this research, a VSC-HVDC was simulated in MATLAB Simulink, and an adjusted VSC-HVDC model was built. The models were applied to simulate the basic operation of VSC-HVDC and main faults on AC and DC side in the VSC-HVDC system. Take line current on AC or DC side as input data, the result data after wavelet processing was applied in HVDC faults diagnosis. To verify the function of fault detection, DC faults at different locations were set in the adjusted model. Wavelet entropy was applied in fault diagnosis and detection to gather accurate results. According to the simulation results, wavelet transform exhibits a good performance in HVDC fault diagnosis and detection.2020-06-0
Supplemental Material - Preference for Smartphone-Based Internet Applications and Smartphone Addiction Among Young Adult Addicts: Gender Difference in Psychological Network
No full textSupplemental Material for Preference for Smartphone-Based Internet Applications and Smartphone Addiction Among Young Adult Addicts: Gender Difference in Psychological Network by Xin-Yi Wei, Han-Yu Liang, Ting Gao, Lingfeng Gao, Guohua Zhang, Xiao-Yuan Chu, Hong-Xia Wang, Jing-Yu Geng, Ke Liu, Jia Nie, Pan Zeng, Lei Ren, Chang Liu, Huai-Bin Jiang, and Li Lei in Social Science Computer Review</p
Cost-effective Scheduling of Load and Microgrid in Wastewater Treatment Plant
No full textABSTRACT COST-EFFECTIVE SCHEDULING OF LOAD AND MICROGRID IN WASTEWATER TREATMENT PLANT By Wentao Zou The University of Wisconsin-Milwaukee,2018 Under the Supervision of Dr. Lingfeng Wang As a big consumer of energy, water and wastewater treatment used about 75000 to 100000 GWh electricity, which accounts for nearly 3% of U.S. annual energy [1]. Not only being energy-intensive, wastewater treatment plant (WWTP) also consumes a lot of electricity during peak hours, which makes WWTP a good candidate of DR (demand response). The main purpose of demand response is to improve the stability of the electric grid and reduce the use of electricity during peak period to lower the total system costs. Two kinds of strategies can be utilized to reduce electrical loads during peak periods, which are load shifting and load shedding. Load shedding strategy is to reduce the total electrical load during demand response event and load shifting is to reschedule the time of some electrical load to partial-peak or off-peak hours. In this work, both of them are used to reach a better financial benefit. The process and energy consumption of WWTP have been analyzed. It is found that the aeration in secondary treatment and pumps for wastewater pumping and sludge pumping are two main processes which consume the majority of total electric power. Based on shifting loads of aerations and pumps, a load shifting model is formulated to shift load from on-peak hours to off-peak hours. Several constraints have been taken into consideration such the storage capacity, maximum holding time of wastewater when it stays in storage tanks, maximum treatment capacity of WWTP, etc. This model can effectively reduce the annual electricity cost while the quality of effluent and the reliability of WWTP are not compromised. In the case study analysis, 22% cost reduction is achieved by using the load shifting model. A software tool has also been developed to help users calculate the amount of cost they can save when the load shifting model is applied. The software tool is user friendly and easy to use. The influent data and electricity price data need to be loaded by users, and some kinds of parameters need to be typed in depending on different situations. For instance, the size of the WWTP and the capacity of storage tank need to be loaded. In addition to demand response, WWTP can save more money with the help of a microgrid. A microgrid is a smaller version of traditional power grid which can provide backup power to WWTP so that the power generated by a microgrid can be used during on-peak hours or sold back to the main grid if possible. A microgrid can also increase the reliability of WWTP. As a discrete energy system with distributed energy sources, a microgrid can operate in parallel with or independently from the main power grid. This feature of the microgrid makes sure WWTP can still receive reliable energy when no electricity can be provided by the main grid. A microgrid model is developed. A battery bank is also involved in the formulation. Constraints including microgrid capacity, charge and discharge efficiency of battery bank, and battery capacity have been considered. The method used to solve this formulation is particle swarm optimization (PSO). A detailed description of the problem-solving process has been displayed step by step. The case study shows the microgrid model can increase the cost reduction further to 29% of total energy expense based on the load shifting model.2019-06-0
Confessions inachevées
No full textde YE Lingfeng 叶灵凤 traduit du chinois par Marie Laureillard YE Lingfeng (1905-1975), né à Nankin, est une figure littéraire importante des années 1920, 1930. D’abord peintre, surnommé le « Beardsley chinois », il adhère à la société littéraire Création, aux côtés de Yu Dafu, son mentor. Il édite plusieurs revues littéraires et publie de nombreux romans dont Wei wancheng de chanhuilu (Confessions inachevées) en 1936. En 1938, il se fixe définitivement à Hong Kong où il poursuit ses activité..
Wen yi sui bi
No full textChapter 第一輯幾本古典名著關於'伊索寓言' ---p.3褒頓與'天方夜譚' ---p.13'十日談','七日談'和'五日談' ---p.20喬叟的'坎特伯雷故事集' ---p.30Chapter 第二輯作家與作品巴爾札克和他的'人間喜劇' ---p.35左拉和他的'盧貢馬加爾家傳' ---p.40史諦芬遜和他的'金銀島' ---p.44霍桑和動人的'紅字'故事 ---p.49莫泊桑的短篇傑作 ---p.53可愛的童話作家安徒生 ---p.58蘇格蘭農民詩人彭斯 ---p.64詩人小說家愛倫坡 ---p.70Chapter 第三輯讀書偶記巴爾札克的'詼諧故事集' ---p.77拉封歹的寓言 ---p.79喬治吉辛和他的散文集 ---p.82淮德的'塞爾彭自然史' ---p.85品托的'遠東旅行記' ---p.88'猴爪'和三個願望的故事 ---p.91意大利的'笑林廣記' ---p.96紀德關於王爾德的回憶 ---p.101'贗幣犯'和'贗幣犯日記' ---p.104潘的性格和故事 ---p.107歌德和席勒的友情 ---p.109艾克曼的'歌德談話錄' ---p.114達爾文和赫胥黎 ---p.117托爾斯泰夫妻失和的內幕 ---p.122Chapter 第四輯幾本書的故事迦撒諾伐和他的'回憶錄' ---p.127王爾德'獄中記'的全文 ---p.131'循環舞'的風波 ---p.137小仲馬和他的'茶花女' ---p.145'茶花女'和茶花女型的故事 ---p.150比亞斯萊,王爾德與'黃面誌' ---p.156'魯濱遜飄流記'的作者 ---p.163'查泰萊夫人之情人'的遭遇 ---p.166'查泰萊夫人之情人'解禁經過 ---p.175後記 ---p.183葉靈鳳著Copy 4 printed in 1979.Ye Lingfeng zh
Corrigendum to 'A phosphorus/silicon-based, hyperbranched polymer for high-performance, fire-safe, transparent epoxy resins' [Polymer Degradation and Stability, 203 (2022) 110065]
No full textThe authors regret that the affiliation of Prof. Zhitian Liu in current manuscript is incorrect. The affiliation of Prof. Zhitian Liu is not ‘Center for Future Materials, University of Southern Queensland, Toowoomba 4350, Australia’, and his affilication is ‘Hubei Engineering Technology Research Center of Optoelectronic and New Energy Materials, School of Materials Science & Engineering, Wuhan Institute of Technology, Wuhan 430205, PR China’. Hence, the author and affilication list should be as follows. Qiu Shia, Siqi Huob, Cheng Wanga, Guofeng Yea, Lingfeng Yua, Zhengping Fangb, Hao Wangc, Zhitian Liua a Hubei Engineering Technology Research Center of Optoelectronic and New Energy Materials, School of Materials Science & Engineering, Wuhan Institute of Technology, Wuhan 430205, PR China b Laboratory of Polymer Materials and Engineering, NingboTech University, Ningbo 315100, PR China c Center for Future Materials, University of Southern Queensland, Toowoomba 4350, Australia The authors would like to apologise for any inconvenience caused
Internal Fault Diagnosis of MMC-HVDC Based on Classification Algorithms in Machine Learning
No full textWith the development of the HVDC system, MMC-HVDC is now the most advanced technology that has been put into use. In power systems, faults happen during the operation due to natural reasons or devices physical issues, which would cause serious economic losses and other implications. Thus, fault detection and analysis are extremely important, especially in the HVDC system. Existing works in literature mainly focus on the faults detection and analysis on the system side such as short circuit of the AC side, and open circuit of the DC side. However, little attention has been paid to the fault detection and analysis inside the converters. With the technology development of converter devices, replacing the whole converter becomes more expensive. Thus, my research mainly focuses on the detection and classification of the faults within the internal of the MMC module. In this research, an SPS model of MMC-HVDC is built as the example. Faults including short circuit and open circuit located inside the MMC module are simulated. Machine learning algorithms are chosen as the tool to achieve the goal of detecting faults and locating the fault position inside the MMC module precisely. After comparing the basic characteristics and properly application situations of various methods of machine learning, Coarse KNN, Complex Tree and Bagged Tree (Random Forest) are deployed to solve the problem. The performance of the methods are analyzed and compared, to get the most proper method in solving the problem.2020-06-1
Model Predictive Control for Mitigating Sensor Attacks on Multilevel Inverters
No full textNowadays, multilevel power inverters have become a hot research topic which are being widely used in smart grids. They are also driving devices for conveyors, compressors, motors, and can enable uninterruptible power supply for critical loads such as database centers or telecommunications base stations. In the future, smart grids will play an important role to achieve higher efficiency, smarter control and better performance. Such an ambitious goal can only be achieved by inverters with higher voltage and power levels. The smart grids are the typical cyber-physical systems that is composed of physical processes and computation units combined by sensors, actuators, and communication devices. The smart grids are apt to errors and vicious attacks on their physical construction leading to considerable damage, such as false data injection (FDI), denial of service (DOS). The vicious data injection can effectively bypass the detection of system and cause serious effects on the grid. In recent years, some advanced control approaches have been proposed to perform inverter current control. Among them, model predictive control (MPC) is a promising one that makes use of explicit system models to predict its future response and optimize system performance. It has unique advantages that can accurately forecast the future response of the system and have fast response. However, the effectiveness and the accuracy of the conventional MPC rely on whether the system model is accurate. Uncertainty and false data injection in the system model sometimes lead to unresponsive or even unstable control systems. Conventional MPC is hard to keep the system stable when the uncertainty and malicious attack happen. In existing studies, although various attacks have been investigated, the undetectable false data injection aiming at the inverter system was rarely studied. In the thesis, the model of the cascaded H-bridge inverter is established and conventional MPC to achieve load current control is applied. It shows great performance to achieve load current control and has fast dynamic control. Then considering various attack signals such as step attack signals, pulse attack signals to the sensors in the system, the conventional MPC loses the ability to achieve a stable and effective current control. According to simulation results, Kalman Filter model is built which can filter some Gaussian noises from the sensors in the system. Then from the perspective of attacker, a special FDI attack is designed that can effectively bypass the Kalman Filter. For the system that targeted by the FDI and DOS attack, a new controller is designed based on the K-Nearest Neighbor (KNN) algorithm and MPC strategy which can achieve the load current control with high output quality. Finally, the new control method based on KNN and MPC is compared with conventional MPC. The simulation results are analyzed and conclusion have been made. A modified MPC combined with KNN algorithm proposed in this thesis can detect bad data that can enter the system without triggering alarms. The case studies show the modified MPC based on KNN algorithm can achieve current control accurately when the system is injected by various attack signals showing better performance of current control with low total harmonic distortion (THD).2020-06-0
Large Scale Integration of Electric Vehicles into the Power Grid and Its Potential Effects on Power System Reliability
No full textIn this thesis, the potential effects of large scale integration of electric vehicles into the power grid are discussed in both the beneficial and detrimental aspects. The literature review gives a comprehensive introduction about the existing smart charging algorithms. According to the system structure and market mechanism, the smart charging algorithms can be divided into centralized and distributed method. With the knowledge of driving patterns and charging characteristics of electric vehicles, both the centralized and decentralized smart charging algorithms are studied in this research. Based on the smart charging pricing and sequential price update mechanism, a multi-agent based distributed smart charging algorithm is used in this research to flatten the load curve and therefore mitigate the potential detrimental effects caused by uncoordinated charging. Each EV agent has some extent of intelligence to solve its own charging scheduling problem. The optimization method used in this research is the binary hybrid GSA-PSO algorithm, which combines the merits of particle swarm optimization (PSO) and gravitational search algorithm (GSA), and has very good exploration and exploitation abilities. A V2G enabled centralized smart charging algorithm is also introduced in this thesis, each EV can earn revenues by discharging power into the grid. The dominant search matrix is used to resolve the ''curse of dimensionality'' problem existing in the centralized optimization problems. Numerical case studies show both the distributed and V2G enabled smart charging algorithms can effectively transfer the charging load from the peak load period to the load valley hours. Because of the limited integration ratio of electric vehicles, most power system reliability methods do not evaluate the charging load of EVs separately in their analytical procedures. However, with a fast increasing integration level, the potential effects of large scale integration of EVs on the power system reliability should be comprehensively evaluated. The effects of EV charging on power system reliability in the planning phase is analyzed in this research based on the RBTS. The results show the uncontrolled charging will deteriorate the reliability level while the smart charging can effectively decrease the detrimental effect. The potential application of aggregated EV providing operating reserve to the grid as a kind of ancillary service is also discussed, and the related effects on power system reliability in operating phase are calculated using the modified PJM method. The case study shows the unit commitment risk of the system can decrease to a very low level with the additional operating reserve capacity provided by aggregated EVs, which can not only improve the system's reliability level but also save the cost.2018-06-0
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