Journal of Modern Power Systems and Clean Energy

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Home > Archive>Volume 11, Issue 5, 2023 >1415-1426. DOI:10.35833/MPCE.2022.000495
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Integrated Equivalent Model of Permanent Magnet Synchronous Generator Based Wind Turbine for Large-scale Offshore Wind Farm Simulation
Author:
Affiliation:

1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University (NCEPU), Beijing, China
2. China Huaneng Group Clean Energy Technology Research Institute Co., Ltd., Beijing, China

Fund Project:

This work was supported by the National Natural Science Foundation of China (No. 52277094) and Science and Technology Project of China Huaneng Group Co., Ltd. (No. HNKJ20-H88).

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    Abstract:

    The high-speed simulation of large-scale offshore wind farms (OWFs) preserving the internal machine information has become a huge challenge due to the large wind turbine (WT) count and microsecond-range time step. Hence, it is undoable to investigate the internal node information of the OWF in the electro-magnetic transient (EMT) programs. To fill this gap, this paper presents an equivalent modeling method for large-scale OWF, whose accuracy and efficiency are guaranteed by integrating the individual devices of permanent magnet synchronous generator (PMSG) based WT. The node-elimination algorithm is used while the internal machine information is recursively updated. Unlike the existing aggregation methods, the developed EMT model can reflect the characteristics of each WT under different wind speeds and WT parameters without modifying the codes. The access to each WT controller is preserved so that the time-varying dynamics of all the WTs could be simulated. Comparisons of the proposed model with the detailed model in PSCAD/EMTDC have shown very high precision and high efficiency. The proposed modeling procedures can be used as reference for other types of WTs once the structures and parameters are given.

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History
  • Received:August 06,2022
  • Revised:October 11,2022
  • Online: September 20,2023

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