Wind turbine state-space model, state estimation and stabilisation algorithms

Rana, M.M., Xiang, W., and Choi, Bong Jun (2018) Wind turbine state-space model, state estimation and stabilisation algorithms. In: Proceedings of the 15th International Conference on Control, Automation, Robotics and Vision. pp. 1235-1240. From: ICARCV 2018: 15th International Conference on Control, Automation, Robotics and Vision, 18-21 November 2018, Singapore.

[img] PDF (Published Version) - Published Version
Restricted to Repository staff only

View at Publisher Website: https://doi.org/10.1109/ICARCV.2018.8581...
 
1


Abstract

This paper develops a state estimation and stabilisation scheme for monitoring and controlling the wind turbine. Basically, the estimation scheme is designed considering the Bayesian tree network. The estimated system states are corrected in the forward and backward direction of this network where the estimation errors are enforced to minimise. Therefore, the estimated system state converges to the actual states as time goes by. Furthermore, the optimal feedback controller is designed. Interestingly, the proposed algorithms are applied to the environment-friendly wind turbine, and it shows that the developed methods can effectively estimate and stabilise the turbine states.

Item ID: 57543
Item Type: Conference Item (Research - E1)
ISBN: 978-1-5386-9582-1
Funders: Ministry of Science and ICT, Korea (MSIT), National Research Foundation of Korea (NRF)
Projects and Grants: MSIT IITP-2017- R0346- 16-1007, NRF-2015R1C1A1A01053788
Date Deposited: 20 Mar 2019 07:40
FoR Codes: 09 ENGINEERING > 0906 Electrical and Electronic Engineering > 090607 Power and Energy Systems Engineering (excl Renewable Power) @ 100%
SEO Codes: 85 ENERGY > 8506 Energy Storage, Distribution and Supply > 850604 Energy Transmission and Distribution (excl. Hydrogen) @ 100%
Downloads: Total: 1
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page