Research Article ActiveandReactivePowerControlforWindTurbinesBasedDFIG Using LQR Controller with Optimal Gain-Scheduling Ashraf Radaideh , Mu’men Bodoor , and Ayman Al-Quraan Electrical Power Engineering Department, Yarmouk University, Irbid, Jordan Correspondence should be addressed to Ashraf Radaideh; a.radaideh@yu.edu.jo Received 19 May 2021; Revised 24 July 2021; Accepted 15 September 2021; Published 6 October 2021 Academic Editor: François Vall´ ee Copyright © 2021 Ashraf Radaideh et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. is paper proposes an optimal gain-scheduling for linear quadratic regulator (LQR) control framework to improve the per- formance of wind turbines based Doubly Fed Induction Generator (DFIG). Active and reactive power decoupling is performed using the field-oriented vector control which is used to simplify DFIG’s nonlinearity and derive a compact linearized state-space model. e performance of the optimal controller represented by a linear quadratic regulator is further enhanced using the whale optimization algorithm in a multiobjective optimization environment. Adaptiveness against wind speed variation is achieved in an offline training process at a discretized wind speed domain. Lookup tables are used to store the optimal controller parameter and called upon during the online implementation. e control framework further integrates the effects of pitch angle control mechanism for active power ancillary services and possible improvements on reactive power support. e results of the proposed control framework improve the overall performance of the system compared to the conventional PI controller. Comparison is performed using the MATLAB Simulink platform. 1. Introduction Electricity is one of the life necessities that made a quantum leap in the world. Traditionally, electrical energy is primarily produced using fossil fuel energy resources. However, nowadays, the world is witnessing high production levels from Renewable Energy Sources (RES). Wind turbines (WTs) are among the leading and fast-growing technologies over extended geographical areas. Worldwide, the total installed capacity in 2019 is 650 GW. More than 93 GW is installed in the year 2020 bringing the total installed capacity to 743 GW despite the COVID-19 pandemic. is indicates the importance and effectiveness of power production using WTs [1]. Wind turbines are initially designed and operated with fixed-speed induction machines to avoid additional costs associated with power electronic converters. However, to improve the conversion efficiency, the variable speed drive system becomes more dominant. Doubly Fed Induction Generator (DFIG) facilitates the variable speed feature through a reduced size converter. is explains the widespread use of DFIGs with wind turbines. DFIG’s stator is directly connected to the grid at the nominal grid frequency and its wound rotor through a bidirectional back-to-back voltage source converters (VSC) but at variable frequency [2, 3]. In many countries, the integration of wind turbines with the grid should follow strict codes and standards. Additional features and capabilities traditionally overlooked have be- come mandatory in new designs such as low voltage ride- through, frequency regulation, and reactive power support. Voltage dips result in large rotor currents due to the high voltages induced in the rotor windings. erefore, DFIGs are very sensitive to voltage sags. Large rotor currents may destroy the Rotor Side Converter (RSC) if not appropriately disconnected by the protection devices. Hence, the wind turbine will be out of service during faulty conditions [4, 5]. 1.1. Related Work. e history of DFIG development in WTS and the different representations of modeling and control techniques are provided in [5]. Modeling and Hindawi Journal of Electrical and Computer Engineering Volume 2021, Article ID 1218236, 19 pages https://doi.org/10.1155/2021/1218236