Based on Multi-Masking Empirical Mode Decomposition (MMEMD) and fuzzy c-means (FCM) clustering, a new method of wind turbine bearing fault diagnosis FCM-MMEMD is proposed, which can determine the fault accurately and ...Based on Multi-Masking Empirical Mode Decomposition (MMEMD) and fuzzy c-means (FCM) clustering, a new method of wind turbine bearing fault diagnosis FCM-MMEMD is proposed, which can determine the fault accurately and timely. First, FCM clustering is employed to classify the data into different clusters, which helps to estimate whether there is a fault and how many fault types there are. If fault signals exist, the fault vibration signals are then demodulated and decomposed into different frequency bands by MMEMD in order to be analyzed further. In order to overcome the mode mixing defect of empirical mode decomposition (EMD), a novel method called MMEMD is proposed. It is an improvement to masking empirical mode decomposition (MEMD). By adding multi-masking signals to the signals to be decomposed in different levels, it can restrain low-frequency components from mixing in highfrequency components effectively in the sifting process and then suppress the mode mixing. It has the advantages of easy implementation and strong ability of suppressing modal mixing. The fault type is determined by Hilbert envelope finally. The results of simulation signal decomposition showed the high performance of MMEMD. Experiments of bearing fault diagnosis in wind turbine bearing fault diagnosis proved the validity and high accuracy of the new method.展开更多
Given factors such as reduced land availability for onshore wind farms,wind resource enrichment levels,and costs,there is a growing trend of establishing wind farms in deserts,the Gobi,and other arid regions.Therefore...Given factors such as reduced land availability for onshore wind farms,wind resource enrichment levels,and costs,there is a growing trend of establishing wind farms in deserts,the Gobi,and other arid regions.Therefore,the relationship between sanddust weather environments and wind turbine operations has garnered significant attention.To investigate the impact of wind turbine wakes on sand-dust transportation,this study employs large eddy simulation to model flow fields,coupled with an actuator line model for simulating rotating blades and a multiphase particle in cell model for simulating sand particles.The research focuses on a horizontal axis wind turbine model and examines the motion and spatiotemporal distribution characteristics of four typical sizes of sand particles in the turbine wake.The findings reveal that sand particles of varying sizes exhibit a spiral settling pattern after traversing the rotating plane of wind turbine blades,influenced by blade shedding vortex and gravity.Sand particles tend to cluster in the peripheries of the vortex cores of low vorticity in the wind turbine wake.The rotation of wind turbines generates a wake vortex structure that causes a significant clustering of sand particles at the tip vortex.As the wake distance increases,the particles that cluster at the turbine's tip gradually spread outward to approximately twice the rotor diameter and then begin to mix with the incoming flow environment.Wind turbines have a noticeable impact on sand-dust transportation,hindering their movement to a significant extent.The average sand-blocking rate exhibits a trend of initially increasing and then decreasing as the wake distance increases.At its peak,the sand-blocking rate reaches an impressive 67.55%.The presence of wind turbines induces the advanced settling of sand particles,resulting in a“triangular”distribution of the deposition within the ground projection area of the wake.展开更多
Offshore wind energy is an important part of clean energy,and the adoption of wind energy to generate electricity will contribute to the implementation of the carbon peaking and carbon neutrality goals.The combination...Offshore wind energy is an important part of clean energy,and the adoption of wind energy to generate electricity will contribute to the implementation of the carbon peaking and carbon neutrality goals.The combination of the fractional frequency transmission system(FFTS) and the direct-drive wind turbine generator will be beneficial to the development of the offshore wind power industry.The use of fractional frequency in FFTS is beneficial to the transmission of electrical energy,but it will also lead to an increase in the volume and weight of the generator,which is unfavorable for wind power generation.Improving the torque density of the generator can effectively reduce the volume of the generators.The vernier permanent magnet machine(VPM) operates on the magnetic flux modulation principle and has the merits of high torque density.In the field of electric machines,the vernier machine based on the principle of magnetic flux modulation has been proved its feasibility to reduce the volume and weight.However,in the field of low-speed direct-drive machines for high-power fractional frequency power generation,there are still few related researches.Therefore,this paper studies the application of magnetic flux modulation in fractional frequency and high-power direct-drive wind turbine generators,mainly analyzes the influence of different pole ratios and different pole pairs on the generator,and draws some conclusions to provide reference for the design of wind turbine generators.展开更多
Electric power conversion system （EPCS）, which consists of a generator and power converter, is one of the most important subsystems in a direct-drive wind turbine （DD-WT）. However, this component accounts for the ...Electric power conversion system （EPCS）, which consists of a generator and power converter, is one of the most important subsystems in a direct-drive wind turbine （DD-WT）. However, this component accounts for the most failures （approximately 60% of the total number） in the entire DD-WT system according to statistical data. To improve the reliability of EPCSs and reduce the operation and maintenance cost of DD-WTs, numerous researchers have studied condition monitoring （CM） and fault diagnostics （FD）. Numerous CM and FD techniques, which have respective advantages and disadvantages, have emerged. This paper provides an overview of the CM, FD, and operation control of EPCSs in DD-WTs under faults. After introducing the functional principle and structure of EPCS, this survey discusses the common failures in wind generators and power converters; briefly reviewed CM and FD methods and operation control of these generators and power converters under faults; and discussed the grid voltage faults related to EPCSs in DD-WTs. These theories and their related technical concepts are systematically discussed. Finally, predicted development trends are presented. The paper provides a valuable reference for developing service quality evaluation methods and fault operation control systems to achieve high-performance and high-intelligence DD-WTs.展开更多
Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet(PM)topologies.Consequently,a comprehensive,accurate,and rapid temperature rise estimation method is required fo...Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet(PM)topologies.Consequently,a comprehensive,accurate,and rapid temperature rise estimation method is required for novel electric machines to ensure safe and reliable operations.A unique three-dimensional(3D)lumped parameter thermal network(LPTN)is presented for accurate thermal modeling of a newly developed outer-rotor hybrid-PM flux switching generator(OR-HPMFSG)for direct-drive applications.First,the losses of the OR-HPMFSG are calculated using 3D finite element analysis(FEA).Subsequently,all machine components considering the thermal contact resistance,anisotropic thermal conductivity of materials,and various heat flow paths are comprehensively modeled based on the thermal resistances.In the proposed 3-D LPTN,internal nodes are considered to predict the average temperature as well as the hot spots of all active and passive components.Experimental measurements are performed on a prototype OR-HPMFSG to validate the efficiency of the 3-D LPTN.A comparison of the results at various operating points between the developed 3-D LPTN,experimental test,and FEA indicates that the 3-D LPTN quickly approximates the hotspot and mean temperature of all components under both transient and steady states with high accuracy.展开更多
Because of the randomness and uncertainty,integration of large-scale wind farms in a power system will exert significant influences on the distribution of power flow.This paper uses polynomial normal transformation me...Because of the randomness and uncertainty,integration of large-scale wind farms in a power system will exert significant influences on the distribution of power flow.This paper uses polynomial normal transformation method to deal with non-normal random variable correlation,and solves probabilistic load flow based on Kriging method.This method is a kind of smallest unbiased variance estimation method which estimates unknown information via employing a point within the confidence scope of weighted linear combination.Compared with traditional approaches which need a greater number of calculation times,long simulation time,and large memory space,Kriging method can rapidly estimate node state variables and branch current power distribution situation.As one of the generator nodes in the western Yunnan power grid,a certain wind farm is chosen for empirical analysis.Results are used to compare with those by Monte Carlo-based accurate solution,which proves the validity and veracity of the model in wind farm power modeling as output of the actual turbine through PSD-BPA.展开更多
基金Supported by National Key R&D Projects(Grant No.2018YFB0905500)National Natural Science Foundation of China(Grant No.51875498)+1 种基金Hebei Provincial Natural Science Foundation of China(Grant Nos.E2018203439,E2018203339,F2016203496)Key Scientific Research Projects Plan of Henan Higher Education Institutions(Grant No.19B460001)
文摘Based on Multi-Masking Empirical Mode Decomposition (MMEMD) and fuzzy c-means (FCM) clustering, a new method of wind turbine bearing fault diagnosis FCM-MMEMD is proposed, which can determine the fault accurately and timely. First, FCM clustering is employed to classify the data into different clusters, which helps to estimate whether there is a fault and how many fault types there are. If fault signals exist, the fault vibration signals are then demodulated and decomposed into different frequency bands by MMEMD in order to be analyzed further. In order to overcome the mode mixing defect of empirical mode decomposition (EMD), a novel method called MMEMD is proposed. It is an improvement to masking empirical mode decomposition (MEMD). By adding multi-masking signals to the signals to be decomposed in different levels, it can restrain low-frequency components from mixing in highfrequency components effectively in the sifting process and then suppress the mode mixing. It has the advantages of easy implementation and strong ability of suppressing modal mixing. The fault type is determined by Hilbert envelope finally. The results of simulation signal decomposition showed the high performance of MMEMD. Experiments of bearing fault diagnosis in wind turbine bearing fault diagnosis proved the validity and high accuracy of the new method.
基金supported by the National Key Research&Development Program of China(Grant Nos.2022YFB4202102,and 2022YFB4202104)the National Natural Science Foundation of China(Grant Nos.52166014,and 52276197)+1 种基金the Science Fund for Creative Research Groups of Gansu Province(Grant No.21JR7RA277)the Hongliu Outstanding Young Talents Program of Lanzhou University of Technology。
文摘Given factors such as reduced land availability for onshore wind farms,wind resource enrichment levels,and costs,there is a growing trend of establishing wind farms in deserts,the Gobi,and other arid regions.Therefore,the relationship between sanddust weather environments and wind turbine operations has garnered significant attention.To investigate the impact of wind turbine wakes on sand-dust transportation,this study employs large eddy simulation to model flow fields,coupled with an actuator line model for simulating rotating blades and a multiphase particle in cell model for simulating sand particles.The research focuses on a horizontal axis wind turbine model and examines the motion and spatiotemporal distribution characteristics of four typical sizes of sand particles in the turbine wake.The findings reveal that sand particles of varying sizes exhibit a spiral settling pattern after traversing the rotating plane of wind turbine blades,influenced by blade shedding vortex and gravity.Sand particles tend to cluster in the peripheries of the vortex cores of low vorticity in the wind turbine wake.The rotation of wind turbines generates a wake vortex structure that causes a significant clustering of sand particles at the tip vortex.As the wake distance increases,the particles that cluster at the turbine's tip gradually spread outward to approximately twice the rotor diameter and then begin to mix with the incoming flow environment.Wind turbines have a noticeable impact on sand-dust transportation,hindering their movement to a significant extent.The average sand-blocking rate exhibits a trend of initially increasing and then decreasing as the wake distance increases.At its peak,the sand-blocking rate reaches an impressive 67.55%.The presence of wind turbines induces the advanced settling of sand particles,resulting in a“triangular”distribution of the deposition within the ground projection area of the wake.
基金supported by the Science and Technology Foundation of SGCC (5500-202099509A-0-0-00)“Research on Fractional Frequency Transmission Technology for Largely Enhancing Transmission Capacity and Development of Its Key Devices”。
文摘Offshore wind energy is an important part of clean energy,and the adoption of wind energy to generate electricity will contribute to the implementation of the carbon peaking and carbon neutrality goals.The combination of the fractional frequency transmission system(FFTS) and the direct-drive wind turbine generator will be beneficial to the development of the offshore wind power industry.The use of fractional frequency in FFTS is beneficial to the transmission of electrical energy,but it will also lead to an increase in the volume and weight of the generator,which is unfavorable for wind power generation.Improving the torque density of the generator can effectively reduce the volume of the generators.The vernier permanent magnet machine(VPM) operates on the magnetic flux modulation principle and has the merits of high torque density.In the field of electric machines,the vernier machine based on the principle of magnetic flux modulation has been proved its feasibility to reduce the volume and weight.However,in the field of low-speed direct-drive machines for high-power fractional frequency power generation,there are still few related researches.Therefore,this paper studies the application of magnetic flux modulation in fractional frequency and high-power direct-drive wind turbine generators,mainly analyzes the influence of different pole ratios and different pole pairs on the generator,and draws some conclusions to provide reference for the design of wind turbine generators.
基金This work was supported by the National Key R＆D Program of China （Grant No. 2016YFF0203400）. The program focuses on studies on service quality monitoring and maintenance quality control technology for large wind turbines. The project leader is Professor Shoudao Huang. The authors are also grateful to the National Natural Science Foundation of China （Grant No. 51377050） for the financial support.
文摘Electric power conversion system （EPCS）, which consists of a generator and power converter, is one of the most important subsystems in a direct-drive wind turbine （DD-WT）. However, this component accounts for the most failures （approximately 60% of the total number） in the entire DD-WT system according to statistical data. To improve the reliability of EPCSs and reduce the operation and maintenance cost of DD-WTs, numerous researchers have studied condition monitoring （CM） and fault diagnostics （FD）. Numerous CM and FD techniques, which have respective advantages and disadvantages, have emerged. This paper provides an overview of the CM, FD, and operation control of EPCSs in DD-WTs under faults. After introducing the functional principle and structure of EPCS, this survey discusses the common failures in wind generators and power converters; briefly reviewed CM and FD methods and operation control of these generators and power converters under faults; and discussed the grid voltage faults related to EPCSs in DD-WTs. These theories and their related technical concepts are systematically discussed. Finally, predicted development trends are presented. The paper provides a valuable reference for developing service quality evaluation methods and fault operation control systems to achieve high-performance and high-intelligence DD-WTs.
文摘Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet(PM)topologies.Consequently,a comprehensive,accurate,and rapid temperature rise estimation method is required for novel electric machines to ensure safe and reliable operations.A unique three-dimensional(3D)lumped parameter thermal network(LPTN)is presented for accurate thermal modeling of a newly developed outer-rotor hybrid-PM flux switching generator(OR-HPMFSG)for direct-drive applications.First,the losses of the OR-HPMFSG are calculated using 3D finite element analysis(FEA).Subsequently,all machine components considering the thermal contact resistance,anisotropic thermal conductivity of materials,and various heat flow paths are comprehensively modeled based on the thermal resistances.In the proposed 3-D LPTN,internal nodes are considered to predict the average temperature as well as the hot spots of all active and passive components.Experimental measurements are performed on a prototype OR-HPMFSG to validate the efficiency of the 3-D LPTN.A comparison of the results at various operating points between the developed 3-D LPTN,experimental test,and FEA indicates that the 3-D LPTN quickly approximates the hotspot and mean temperature of all components under both transient and steady states with high accuracy.
文摘Because of the randomness and uncertainty,integration of large-scale wind farms in a power system will exert significant influences on the distribution of power flow.This paper uses polynomial normal transformation method to deal with non-normal random variable correlation,and solves probabilistic load flow based on Kriging method.This method is a kind of smallest unbiased variance estimation method which estimates unknown information via employing a point within the confidence scope of weighted linear combination.Compared with traditional approaches which need a greater number of calculation times,long simulation time,and large memory space,Kriging method can rapidly estimate node state variables and branch current power distribution situation.As one of the generator nodes in the western Yunnan power grid,a certain wind farm is chosen for empirical analysis.Results are used to compare with those by Monte Carlo-based accurate solution,which proves the validity and veracity of the model in wind farm power modeling as output of the actual turbine through PSD-BPA.
