Open AccessNonlinear Predictive Control Method for Maximizing Wind Energy Extraction of Variable Speed Wind Turbines under Turbulence
Author(s) -
Ahmed Aissaoui,
Houari Khouidmi,
Ahmed Benzouaoui,
Boubaker Bessedik
Publication year - 2021
Publication title -
journal européen des systèmes automatisés/journal européen des systèmes automaitsés
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.16
H-Index - 20
eISSN - 2116-7087
pISSN - 1269-6935
DOI - 10.18280/jesa.540501
Subject(s) - wind power , control theory (sociology) , maximum power point tracking , wind speed , maximum power principle , nonlinear system , turbine , rotor (electric) , tip speed ratio , computer science , model predictive control , aerodynamics , power optimizer , torque , engineering , control (management) , artificial intelligence , meteorology , voltage , physics , mechanical engineering , quantum mechanics , inverter , aerospace engineering , electrical engineering , thermodynamics
Generally, wind turbines are controlled by Maximum Power Point Tracking (MPPT) strategies in order to achieve maximum power extraction below its rated value. But it is very difficult to adjust the rotor speed according to the highly fluctuating wind speed accurately and quickly, due to the large inertia of wind turbines, and therefore, the efficiency of wind energy extraction will never reach its theoretical maximum value. To address this problem, a new method has been developed in this paper which is totally different from the known classical methods. In this paper a wind speeds prediction for maximum wind energy extraction (MWEE) of variable-speed wind turbines (VSWTs) is presented. A nonlinear predictive control is developed by solving a nonlinear optimization problem to generate the optimal generator torque sequence and consequently the previewed rotor speeds with maximum wind energy extraction. A detailed explanation has been provided of how this new method works through a detailed block diagram; accurate algorithm and flowchart. The proposed nonlinear predictive method takes full advantage and the MWEE objective is confirmed by the simulation results compared to the classical TSR methods.