Programs
- M. Tech. in Automotive Engineering -
- Fellowship In Interventional Pulmonology and Pulmonary Critical care - Fellowship
Publication Type : Journal Article
Source : Proc. International Conference on Advances in Computing, Communications and Informatics, 2017
Url : https://ieeexplore.ieee.org/abstract/document/8125866
Campus : Coimbatore
School : School of Engineering
Department : Electronics and Communication
Year : 2017
Abstract : In wind turbine, the third power of the wind speed is directly proportional to the power produced due to the wind. Hence the power produced increases with respect to the wind speed. By using an appropriate generator torque, the system can optimize the conversion of wind energy. During high wind speeds, wind turbine power has to be constrained. Approximating the system states by processing the input data is called as state estimation. We are using this state estimation for the estimation of wind turbine parameters. The wind speeds are the most mandatory among them all to be estimated. For a set of conditions, state estimation techniques can be used to track the wind turbine parameters. A nonlinear state estimator, particle filter, is introduced and explained. The particle filter is implemented for estimating the wind turbine parameters: tower top displacement, tower Stop velocity and the rotor speed. The resultant performance is tested and verified with the simulation results. Particle filter is the most popular approach. The main reason why particle filters are so accepted is that it is very flexible and adaptive.
Cite this Research Publication : Sudev, P., Anita, J.P., and Sudheesh, P, “Nonlinear state estimation of wind turbine”, Proc. International Conference on Advances in Computing, Communications and Informatics, 2017.