Adaptive linear prediction for optimal control of wind turbines. (December 2017)

• Record Type: Journal Article
• Authors: Narayana, Mahinsasa; Sunderland, Keith M.; Putrus, Ghanim; Conlon, Michael F.
• Is Part Of: Renewable energy. Volume 113(2017)
• Page Start: 895
• Page End: 906
• Publication Date: 2017-12
• Subjects: Wind energy conversion systems -- Wind turbine -- Linear adaptive prediction -- Power mapping technique -- Wind speed sensor technique -- Wind speed estimation; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2017.06.041
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: In order to obtain maximum power output of a Wind Energy Conversion System (WECS), the rotor speed needs to be optimised for a particular wind speed. However, due to inherent inertia, the rotor of a WECS cannot react instantaneously according to wind speed variations. As a consequence, the performance of the system and consequently the wind energy conversion capability of the rotor are negatively affected. This study considers the use of a time series Adaptive Linear Prediction (ALP) technique as a means to improve the performance and conversion efficiency of wind turbines. The ALP technique is introduced as a real time control reference to improve optimal control of wind turbines. In this study, a wind turbine emulator is developed to evaluate the performance of the predictive control strategy. In this regard, the ALP reference control method was applied as a means to control the torque/speed of the emulator. The results show that the employment of a predictive technique increases energy yield by almost 5%. Highlights: A representation of the performance of a real wind turbine subjected to variable wind. Adaptive Linear Prediction to improve performance and conversion efficiencies of WECS. Wind turbine emulator as a means to evaluate time series linear prediction. Wind sensor method offers an optimal power mapping technique.