Control of wind turbine above rated wind speed using improved fuzzy logic and model predictive control

Authors

  • Satyabrata Sahoo Research scholar, Utkal University, Bhubaneswar, Odisha, India
  • Bidyadhar Subudhi Department of Electrical Engineering, National Institute of Technology Rourkela, India.
  • Gayadhar Panda Department of Electrical Engineering, National Institute of Technology Meghalaya, India

Abstract

This paper focuses on the design of improved fuzzy logic and model predictive control schemes employed for pitch angle regulation of wind energy conversion system (WECS). Due to rotation of earth, the speed of wind on the earth’s surface changes continuously. As a result, the power generated fromWECS varies. This generated power fromWECS depends on cube of the wind speed and it leads to the power fluctuations. Pertaining to the stable power output from WECS under varying wind speed, a number of control techniques are developed in the literature over the last few years. Presently for regulation of output power fluctuations against variable wind speed environment, pitch angle control is extensively used. In view of handling the uncertainties owing to wind speed variations, this study exhibits the comparative performance of Improved Fuzzy logic control (IFLC) and Model predictive control (MPC) schemes by modeling and simulating the WECS via MATLAB/Simulink. The main control objective is to keep the power generation within the rated power of the generator against wind speed variation, which can be achieved by regulating the pitch angle and/or generator torque. To assess the capability of MPC scheme, theWECS is modeled and simulated under different wind speed test cases. From the obtained results, it is confirmed that the response of MPC is better than IFLC, in situation of wind speed variations.

Keywords:Wind Energy Conversion System; Improved Fuzzy Logic Control; Power quality; Model Predictive Control.

Cite As

S. Sahoo, B. Subudhi, G. Panda, "Control of wind turbine above rated wind speed using improved fuzzy logic and
model predictive control.", Engineering Intelligent Systems, vol. 26 no. 1, pp. 11-20, 2018.



Downloads

Published

2018-03-01

Issue

Vol. 26 No. 1 (2018): International Journal of Engineering Intelligent Systems

Section

General Submission

License

The submission of a paper implies that, if accepted for publication, it will not be published elsewhere in the same form, in any language, without the prior consent of the publisher. Before publication, authors are requested to assign copyright to CRL Publishing Ltd. This allows CRL to sanction photocopying, and to authorize the reprinting of issues or volumes according to demand. Authors' traditional rights will not be jeopardized by assigning Copyright in this way, as they retain the right to reuse the material following publication, and to veto third-party publication.