Optimization of Dual-Drive Modeling for Large-Scale Offshore Wind Farms

This paper introduced the new achievement from the research on optimization of dual-drive modelling technology for large-scale offshore wind farms. The dual-drive model consisted of data driven and knowledge driven respectively, and the iterative optimization is carried out by multi-parameter optimi...

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Bibliographic Details
Published in2024 IEEE 7th International Electrical and Energy Conference (CIEEC) pp. 20 - 25
Main Authors Zhang, Junyang, Guo, Xiaojiang, Yao, Zhongyuan, Li, Zheng, Zhao, Jianjian, Chen, Yijing
Format Conference Proceeding
LanguageEnglish
Published IEEE 10.05.2024
Subjects
Analytical models
Data driven
Data models
Digital twins
Heuristic algorithms
Knowledge driven
Multi-parameter optimization
Neural network
Offshore wind power
Power system dynamics
Real-time simulation
Real-time systems
Wind farms
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Summary:This paper introduced the new achievement from the research on optimization of dual-drive modelling technology for large-scale offshore wind farms. The dual-drive model consisted of data driven and knowledge driven respectively, and the iterative optimization is carried out by multi-parameter optimization neural network algorithm. Virtual twin model is a real-time simulation system formed by dual-drive simulation optimization algorithm, which takes multi-dimensional and multi-body dynamics modelling and multi-time scale simulation calculation as the basis, integrates multiple disciplines simulation and artificial intelligence algorithms, and combines renewable energy generation and integration as a significant result. The large-scale offshore wind farm real-time simulation model has improved the architecture of traditional electromagnetic transient digital simulation of power system.
DOI:10.1109/CIEEC60922.2024.10583005