Advanced adaptive frequency support scheme for DFIG under cyber uncertainty

Huaizhi Wang, Yangyang Liu, Bin Zhou, Nikolai Voropai, Guangzhong Cao, Youwei Jia and Evgeny Barakhtenko

Renewable Energy, 2020, vol. 161, issue C, 98-109

Abstract: In recent years, the development of information and communication technology has promoted the transformation of traditional electrical power grid into a deeply-intertwined cyber physical power system (CPPS). However, it also introduces cyber uncertainties that have a significant impact on the economic operation and real-time control of CPPS. This paper aims to solve the control problem of frequency support of wind farms in a cyber uncertainty environment, and proposes an advanced adaptive frequency support scheme for doubly-fed induction generator (DFIG). In the proposed scheme, both the minimum rotor speed and the deloaded operating level of wind turbines are required to be determined at first. Then, an advanced adaptive droop control method is proposed with consideration of cyber uncertainty to improve the response speed of wind turbines for frequency support. Finally, the stability of the proposed scheme is theoretically proved. The proposed scheme combines deloading control and inertial control, so that the controller can not only make up for the impact of cyber uncertainty on frequency regulation, but also can adaptively determine the participation factor of each wind turbine. The effectiveness of this control scheme is highlighted on a simulation platform built on Matlab/Simulink. The obtained results demonstrate that the proposed control scheme is capable for improving the frequency nadir and preventing secondary frequency dips.

Keywords: DFIG; Frequency support; Droop control; Cyber uncertainty; Cyber physical power system (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:161:y:2020:i:c:p:98-109

DOI: 10.1016/j.renene.2020.06.085

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