The results of evaluation standards such as accuracy rate, missed detection rate and F1-measure show that the proposed algorithm can solve the problem of multi-classification fault diagnosis
The diagnosis of faults in wind turbine gearboxes based on signal processing represents a significant area of research within the field of wind power generation. This paper presents an intelligent fault diagnosis method
The 14th International Conference on Developments in Power System Protection (DPSP 2018) Fault current control methods for multi- the active synchronous generation or an offshore
The generated power can not be modified as it is limited because of the voltage drop during the fault. However, the reference power can be adapted according to the fault severity. Adaptation of power reference is
Wind energy, as a clean and renewable energy source, not only is it dispatchable according to changes in wind speed, but the construction of wind power projects creates local
From the wind turbine system structure diagram of Fig. 2 and the Table 1 sensor information table, we can further understand the main structure of the wind power generation.
The proposed optimal power dispatch strategy was compared with the two generally-used fault-handling methods and the proportional dispatch strategy in simulation. The result shows that
To improve the fault redundancy capability for the high reliability requirement of a brushless doubly-fed generation system applied to large offshore wind farms, the control
2 天之前· The presence of missing values in the data poses challenges for fault detection tasks in wind power processes. The conventional data filling methods commonly focus on the process
Long et al. proposed a fault diagnosis method for wind turbine gearboxes based on a particle swarm optimization BP neural network, and extracted the power spectrum entropy and wavelet entropy of the gearbox as
The proposed optimal power dispatch strategy was compared with the two generally-used fault-handling methods and the proportional dispatch strategy in simulation. The result shows that the proposed strategy can
This paper first discusses the challenges of using SCADA to support generator fault prediction and diagnosis. It then presents an unsupervised learning method to perform generator fault
In, a fault diagnosis method was presented for multiple open-circuit faults in back-to-back converters of a permanent magnet synchronous generator (PMSG) drive for wind turbine systems where a Luenberger
Voltage source converter based high voltage direct current(VSC-HVDC)system is a relatively good choice for the grid integration of large-scale wind farms.When faults occur in the AC
Wind turbine bearings are one of the most important components of wind turbine generating equipment. Failure problems in wind turbine bearings can affect the operation of
Methods for Wind Turbine Fault Diagnosis. Front. Energy Res. 9:751066. in major wind power generation industries (Dao et al., 2018). Compared with European and American countries,
of model-based, signal-based, knowledge-based and hybrid approaches to wind turbine generator fault diagnosis is summarized. The comprehensive review shows that the hybrid approach is
Validity of the proposed method proposed is verified by pratical fault diagnosis application of wind turbine. Operation of wind turbines under fault state will directly affect the power output efficiency of wind farms. This paper proposes a new automatic fault diagnosis method for wind turbines.
A framework on the fault diagnosis of wind power generation was proposed. Through the constructed fault diagnosis system, large amount of data of vibrations status of wind turbines was collected and processed for fault diagnosis of wind turbines.
Using these simplified models, some fault detection methods have been proposed and applied effectively in the wind turbine system as the reference papers [6, 11, 14, 20, 22, 23], in which fault identification can be easily tested and validated.
Wang D et al (2023) A correlation-graph-CNN method for fault diagnosis of wind turbine based on state tracking and data driving model. Sustain Energy Technol Assess 56:102995 Ding SX (2014) Data-driven design of fault diagnosis and fault-tolerant control systems. Springer, Berlin
Operation of wind turbines under fault state will directly affect the power output efficiency of wind farms. This paper proposes a new automatic fault diagnosis method for wind turbines. A fault diagnosis system framework is constructed and data of vibration status of wind turbines collected is processed and used for fault diagnosis.
This paper presents the study of fault handling capability of wind turbines with several grid-forming control strategies. In this context, four different control schemes i.e. Visynch, P/f droop, Q/f droop and conventional grid following control are considered.
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