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Download fileAn Extreme Learning Machine-Based System Frequency Nadir Constraint Linearization Method
preprint
posted on 2021-08-12, 17:04 authored by Likai LiuLikai Liu, Zechun Hu, Nikhil Pathak, Haocheng LuoLarge-scale
integration of converter-based renewable energy sources (RESs) into the power system will
lead to a higher risk of frequency nadir limit violation and even frequency
instability after the large power disturbance. Therefore, it is essential to
consider the frequency nadir constraint (FNC) in power system scheduling.
Nevertheless, the FNC is highly nonlinear and nonconvex. The state-of-the-art method to simplify the constraint is
to construct a low-order frequency response model at first, and then linearize the frequency
nadir equation. In this letter, an extreme
learning machine (ELM)-based network is built to derive the linear
formulation of FNC, where the two-step fitting process is integrated into one
training process and more details about the physical model of the generator are considered to reduce the fitting error.
Simulation results show the superiority
of the proposed method on the fitting accuracy.
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Email Address of Submitting Author
llk17@mails.tsinghua.edu.cnSubmitting Author's Institution
Tsinghua UniversitySubmitting Author's Country
- China