期刊
ENERGY REPORTS
卷 9, 期 -, 页码 288-298出版社
ELSEVIER
DOI: 10.1016/j.egyr.2023.04.059
关键词
Hybrid energy storage system; Virtual inertia control; Virtual synchronous generator; Butterworth filter
The paper proposes an inertia adaptive control method based on the power complementary characteristics of supercapacitors and batteries to address the frequency stability issue caused by the large-scale access of new energy to the power grid. By using virtual inertia voltage control and virtual synchronous generator control, the power output of supercapacitors and hybrid energy storage systems are regulated to achieve smooth switching and ensure voltage and frequency stability.
The large-scale access of new energy to the power grid leads to a significant decrease in the inertia level of the power system, which seriously threatens the system frequency stability. By considering the power complementary characteristics of the supercapacitor and battery, an inertia adaptive control is proposed based on the amplitude-frequency characteristic curves of the Butterworth filter to integrate the inertia level of the system. For this strategy, the virtual inertia voltage control is used to adjust the power output of the supercapacitor to smooth the high-frequency disturbance and imitate the inertia response of the synchronous generators (SGs), which can reduce the number of SGs movements near the dead zone, and at the same time, the virtual synchronous generator (VSG) control is adopted to regulate the power output of the hybrid energy storage system (HESS) to participate in primary frequency regulation. The notable feature of this method is to achieve a smooth switching between the virtual inertia voltage control of the supercapacitor and the VSG control, which can ensure the DC side voltage level and AC side grid frequency level, by constructing an adaptive control model of inertia weight coefficients according to the Butterworth filter. Finally, a regional frequency regulation model with the HESS is built under the MATLAB/SIMULINK environment to verify the effectiveness of the proposed approach. (c) 2023 The Authors. Published by Elsevier Ltd. This is an open access article under theCCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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