Adaptive linear prediction for optimal control of wind turbines

Mahinsasa Narayana, Keith Sunderland, Ghanim Putrus, Michael Conlon

    Research output: Contribution to journalArticlepeer-review

    34 Citations (Scopus)

    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%.
    Original languageEnglish
    Pages (from-to)895-906
    JournalRenewable Energy
    Volume113
    Early online date10 Jun 2017
    DOIs
    Publication statusPublished - 1 Dec 2017

    Keywords

    • linear adaptive prediction
    • power mapping technique
    • wind speed sensor technique
    • wind speed estimation

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