scholarly journals Stability analysis for direct‐drive permanent magnet synchronous generator based wind farm integration system considering wind speed

2020 ◽  
Vol 14 (11) ◽  
pp. 1894-1903
Author(s):  
Xiaoming Zou ◽  
Xiong Du ◽  
Heng‐Ming Tai
Keyword(s):  
Stability Analysis ◽  
Wind Speed ◽  
Permanent Magnet ◽  
Wind Farm ◽  
Synchronous Generator ◽  
Direct Drive ◽  
Permanent Magnet Synchronous Generator ◽  
Integration System ◽  
Wind Farm Integration

Direct liquid cooling for an outer‐rotor direct‐drive permanent‐magnet synchronous generator for wind farm applications

2015 ◽  
Vol 9 (8) ◽  
pp. 523-532 ◽  
Author(s):  
Maria Polikarpova ◽  
Pavel Ponomarev ◽  
Pekka Röyttä ◽  
Scott Semken ◽  
Yulia Alexandrova ◽  
...  
Keyword(s):  
Permanent Magnet ◽  
Wind Farm ◽  
Synchronous Generator ◽  
Direct Drive ◽  
Liquid Cooling ◽  
Permanent Magnet Synchronous Generator ◽  
Outer Rotor

Design and optimization of permanent magnet synchronous generator dedicated to direct-drive, high power wind turbine

2021 ◽  
pp. 0309524X2110463
Author(s):  
Dorra Abdeljalil ◽  
Mohamed Chaieb ◽  
Naourez Benhadj ◽  
Manel Krichen ◽  
Rafik Neji
Keyword(s):  
Finite Element ◽  
Wind Turbine ◽  
Permanent Magnet ◽  
High Power ◽  
Large Scale ◽  
Wind Farm ◽  
Synchronous Generator ◽  
Direct Drive ◽  
Permanent Magnet Synchronous Generator ◽  
Design And Optimization

This paper presents analysis, design, and optimization of a high-power permanent-magnet synchronous generator (PMSG). This generator is introduced in a large-scale wind turbine which can be used in a big wind farm. This generator is used in gearless configuration. The work focuses on the geometric sizing and the finite element analysis (FEA) of the PMSG. FEA is a good choice for analyzing problems over complicated domains. The flux, the electromotive force, the cogging torque, and the torque are calculated using analytical equations. Then, these parameters are obtained using finite element method (FEM) in the software FEMM and the compared with analytical results in order to validate our study. The second part presents the formulation of the optimization problem, including the optimization space, constraints, and objectives. The genetic algorithm (GA) is adopted in this design optimization in order to minimize the generator cost.

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