논문 해외 국제전문학술지(SCI급) A design of the Real-time Simulation for wind turbine modelling based on machine learning
- 학술지 구분 국제전문학술지(SCI급)
- 게재년월 2023
- 저자명 J.-H. Kim, R.-J. Park, S. Kang, S. Cho, S.Jung
- 학술지명 Journal of Electrical Engineering & Technology
- 발행처명 Springer Nature
- 발행국가 해외
- 논문언어 외국어
홈페이지논문 초록 (Abstract)
Power system operators have recently introduced some AI-based techniques in load prediction, fault diagnosis, scheduling, and maintenance. Operators require a grid analysis that includes wind turbines to mitigate impacts by environmental factors. Among them, a method for modeling wind turbines that reflects the dynamic characteristics and their output characteristics is receiving attention. Recently, a data-based power curve modeling method has been adopted for a simplified model that characteristics as much as possible. However, the simplified EMT simulation is difficult to reflect the output characteristics according to nonlinear wind conditions accurately. This paper proposes a wind turbine model based on artificial neural network techniques using real supervisory control and data acquisition (SCADA) data from a wind farm. The proposed strategy derive the similar to real output value through the trained wind turbine model in various wind scenarios. For the verification of the proposed strategy, the case study was conducted using a real-time digital simulator (RTDS).