Design, Implementation, and Evaluation of an Output Prediction Model of the 10 MW Floating Offshore Wind Turbine for a Digital Twinopen access
- Authors
- Kim, Changhyun; Dinh, Minh-Chau; Sung, Hae-Jin; Kim, Kyong-Hwan; Choi, Jeong-Ho; Graber, Lukas; Yu, In-Keun; Park, Minwon
- Issue Date
- 9월-2022
- Publisher
- MDPI
- Keywords
- digital twin; hybrid analysis and modeling; reduce order model; offshore wind turbine
- Citation
- ENERGIES, v.15, no.17
- Journal Title
- ENERGIES
- Volume
- 15
- Number
- 17
- URI
- https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/9605
- DOI
- 10.3390/en15176329
- ISSN
- 1996-1073
1996-1073
- Abstract
- 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.
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