Adaptive filtering with robust controller for improvement of inertial response of wind turbine

Seyed Reza Aali | Mohammadreza Besmi | Mohammad Hosein Kazemi

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URL :   http://research.shahed.ac.ir/WSR/WebPages/Report/PaperView.aspx?PaperID=116847
Date :  2019/09/16
Publish in :    International Transactions on Electrical Energy Systems
DOI :  https://doi.org/10.1002/2050-7038.12089
Link :  http://dx.doi.org/10.1002/2050-7038.12089
Keywords :ACLMS algorithm, adaptive filtering, delayed signal cancelation phase?locked loop (DSC?PLL), doubly fed induction generator (DFIG), frequency control, H??robust controller, virtual inertia control

Abstract :

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It is necessary to study the impact of large‐scale wind turbines with virtual inertia control on power system stability considering the effects of frequency measurement. The phase‐locked loop (PLL) measures the system frequency. The operation of the PLL is deteriorated when the voltage contains sags, unbalance, high harmonics, and sudden drop frequency. Cascaded delayed signal cancelation (DSC) PLL technique can be used for frequency measurement under nonideal voltage due to its good harmonics filtering capability. But there are some oscillations and errors in the frequency estimation by the DSC‐PLL that led not to suitable frequency control in a doubly fed induction generator (DFIG). In this paper, an adaptive complex least mean square (ACLMS) algorithm is used for frequency estimation. The ACLMS algorithm is an adaptive filter, which can track frequency deviation, accurately and rapidly. In addition, this paper addresses robust frequency control in the DFIG. In a power system with wind turbines, load change, power fluctuation disturbance, and a dynamical perturbation influence the system frequency. In this condition, the conventional‐inertia controller is faced with challenges. H∞‐robust controller develops the frequency control loop. The estimated frequency using the ACLMS algorithm feeds the robust controller to improve the inertial response of the DFIG. This paper compares between H∞ and optimal conventional‐based inertia controller. The simulation validates that the ACLMS estimation with the H∞ inertia controller simultaneously provides frequency support to a low‐inertia tested power system, effectively. It improves frequency stability and resiliency under different disturbances and uncertainty.