A new predictive control strategy for improving operating performance of a permanent magnet synchronous generator-based wind energy and superconducting magnetic energy storage hybrid system integrated with grid

被引:11
|
作者
Mughees, Neelam [1 ,2 ]
Jaffery, Mujtaba Hussain [1 ]
Jawad, Muhammad [1 ]
机构
[1] COMSATS Univ Islamabad CUI, Dept Elect & Comp Engn, Lahore Campus, Islamabad 45550, Pakistan
[2] Natl Text Univ, Sch Engn & Technol, Faisalabad 37610, Pakistan
关键词
Unscented Kalman filter; Predictive current control; Wind energy conversion system; Superconducting magnetic energy storage; FOPI controllers; FIELD-ORIENTED CONTROL; BACK-EMF; SENSORLESS CONTROL; NEURAL-NETWORKS; TURBINE; PMSM; OBSERVER; VECTOR; TORQUE;
D O I
10.1016/j.est.2022.105515
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This research work proposes an unscented Kalman filter (UKF) as an observer for predictive current control (PCC) of a permanent magnetic synchronous generator (PMSG)-based wind energy conversion system (WECS) con-nected with a superconducting magnetic energy storage (SMES) system and the main power grid. The proposed UKF observer estimates the rotor angle, rotor angular speed, stator currents, and electromagnetic torque of PMSG connected in the proposed hybrid WECS-SMES configuration. The PCCs designed for both the rotor-and grid -side converters of the proposed hybrid configuration use estimated parameters instead of the measured quan-tities. Furthermore, due to the intermittent nature of wind energy, control of an energy storage device (which is SMES in this research) is necessary to mitigate the fluctuations in the DC-link voltage and output power being sent to the main power grid. Therefore, a novel control configuration based on fractional order-PI (FOPI) con-trollers has also been proposed for the SMES system to control the output power and the DC-link voltage. An artificial bee colony optimization algorithm has been used to tune the gains and integration operators of two FOPI controllers. For UKF estimation performance comparison, three popular observers i.e., Luenberger, sliding mode, and extended Kalman filter, have also been designed and implemented in MATLAB. Mean absolute per-centage error and root mean squared error performance metrics are used to measure the estimation performance. The simulated results have demonstrated the superior performance of proposed the UKF observer for PCC and FOPI controllers for SMES under different realistic wind speed conditions and noisy measurements. The proposed UKF observer has improved estimation by up to 99.9 %. Lyapunov stability criteria are used to prove the stability of the proposed UKF based PCC control of hybrid WECS-SMES configuration.
引用
收藏
页数:17
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