Design, Implementation, and Evaluation of an Output Prediction Model of the 10 MW Floating Offshore Wind Turbine for a Digital Twin

Predicting the output power of wind generators is essential to improve grid flexibility, which is vulnerable to power supply variability and uncertainty. Digital twins can help predict the output of a wind turbine using a variety of environmental data generated by real-world systems. This paper deal...

Full description

Saved in:
Bibliographic Details
Published inEnergies (Basel) Vol. 15; no. 17; p. 6329
Main Authors Kim, Changhyun, Dinh, Minh-Chau, Sung, Hae-Jin, Kim, Kyong-Hwan, Choi, Jeong-Ho, Graber, Lukas, Yu, In-Keun, Park, Minwon
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.09.2022
Subjects
Accuracy
Air-turbines
Alternative energy sources
Analysis
digital twin
Digital twins
Electric utilities
Electricity distribution
Fault diagnosis
Flexibility
hybrid analysis and modeling
Machine learning
Marine environment
Offshore
Offshore energy sources
Offshore operations
offshore wind turbine
Physics
Prediction models
Real time
reduce order model
Renewable resources
Turbines
Twins
Wind power
South Korea
Online AccessGet full text

Cover

More Information
Summary:Predicting the output power of wind generators is essential to improve grid flexibility, which is vulnerable to power supply variability and uncertainty. Digital twins can help predict the output of a wind turbine using a variety of environmental data generated by real-world systems. This paper dealt with the development of a physics-based output prediction model (P-bOPM) for a 10 MW floating offshore wind turbine (FOWT) for a digital twin. The wind power generator dealt with in this paper was modeled considering the NREL 5 MW standard wind turbine with a semi-submersible structure. A P-bOPM of a 10 MW FOWT for a digital twin was designed and simulated using ANSYS Twin Builder. By connecting the P-bOPM developed for the digital twin implementation with an external sensor through TCP/IP communication, it was possible to calculate the output of the wind turbine using real-time field data. As a result of evaluating the P-bOPM for various marine environments, it showed good accuracy. The digital twin equipped with the P-bOPM, which accurately reflects the variability of the offshore wind farm and can predict the output in real time, will be a great help in improving the flexibility of the power system in the future.
ISSN:1996-1073
1996-1073
DOI:10.3390/en15176329