Open AccessAugmented system for detecting the steady‐state voltage stability margin
Author(s) -
Wan Kaiyao,
Jiang Tong
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2020.0713
Subject(s) - control theory (sociology) , bifurcation , margin (machine learning) , mathematics , saddle node bifurcation , equilibrium point , manifold (fluid mechanics) , tangent vector , continuation , limit (mathematics) , steady state (chemistry) , saddle point , tangent , electric power system , power (physics) , mathematical analysis , computer science , differential equation , physics , geometry , engineering , nonlinear system , chemistry , artificial intelligence , control (management) , quantum mechanics , machine learning , programming language , mechanical engineering
This work provides an augmented system (AS), constructed based on a modified tangent vector Index, i.e. the full derivative of the uncontrollable parameter with respect to the voltage magnitude of critical bus of the system, to directly detect steady‐state voltage stability margin (SSVSM). The Newton iteration produced by the AS is illustrated to be able to approach the equilibrium manifold until converging to the saddle node bifurcation, given that the initial point is approaching to the corresponding branch. With the special searching direction, limit induced dynamic bifurcations or limit induced static bifurcation that appear along the equilibrium manifold are able to be located with expected precision by the proposed corrections. Several cases in a 2000‐bus synthetic grid exemplify the effectiveness and high efficiency of the algorithm, compared with standard continuation power flow and the predicter‐corrector primal dual interior point algorithm for detecting the SSVSM.