Comparison of Output Power Control Performance of Wind Turbine using PI, Fuzzy Logic and Model Predictive Controllers

satyabrata sahoo, Bidyadhar Subudhi, Gayadhar Panda

Abstract


In the variable speed wind energy conversion system, one of the operational problems is to handle the speed uncertainty and discontinuity of wind, that influence the power generation from a wind energy conversion systems (WECS). In order achieve a stable power output from a WECS despite variations in the wind speed, a number of control algorithms were devised in the literature over the past few years. Pitch angle control is widely used for regulation of output power fluctuations in a WECS. The control objective is to maintain stable power generation against wind speed variation, which can be achieved by regulating the pitch angle and/or generator torque. In view of handling the uncertainties owing to wind speed variations, this paper pursued a comparative assessment of three controllers, namely Proportional-Integral control, Fuzzy logic control (FLC) and Model predictive control (MPC) schemes. To evaluate their performance a simulation setup for implementing these three controllers applied to a WECS is prepared in MATLAB/Simulink. From the obtained results, it is envisaged that the proposed MPC exhibits excellent response and robustness of the WECS in face of uncertainties owing to intermittency and discontinuity of the wind speed.

Keywords


Wind Energy Conversion System; Fuzzy Logic Controller; power quality; Fuzzy Inference System; Model Predictive Control (MPC), Step Wind Speed

Full Text:

PDF


DOI (PDF): https://doi.org/10.20508/ijrer.v8i2.6934.g7392

Refbacks

  • There are currently no refbacks.


Online ISSN: 1309-0127

Publisher: Gazi University

IJRER is cited in SCOPUS, EBSCO, WEB of SCIENCE (Clarivate Analytics);

IJRER has been cited in Emerging Sources Citation Index from 2016 in web of science.

WEB of SCIENCE between 2020-2022; 

h=30,

Average citation per item=5.73

Impact Factor=(1638+1731+1808)/(189+170+221)=9.24

Category Quartile:Q4