Open AccessPOWER SYSTEM CONTINGENCY RANKING BASED ON SHORT-TERM VOLTAGE STABILITY INDICES
Author(s) -
Jaime Dwaigth Pinzon Casallas,
D. G. ColomÃ
Publication year - 2019
Publication title -
latin american applied research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.123
H-Index - 23
eISSN - 1851-8796
pISSN - 0327-0793
DOI - 10.52292/j.laar.2019.92
Subject(s) - contingency , electric power system , term (time) , stability (learning theory) , contingency table , control theory (sociology) , voltage , ranking (information retrieval) , identification (biology) , computer science , lyapunov function , reliability engineering , power (physics) , mathematics , statistics , engineering , artificial intelligence , machine learning , control (management) , electrical engineering , philosophy , linguistics , physics , botany , quantum mechanics , nonlinear system , biology
This paper presents a novel methodology to identify critical contingencies that produce short-term voltage stability problems (STVS). The proposed methodology classifies the state of the pow-er system for each contingency, assessing the voltage stability of the post-contingency dynamic response from the calculation of the maximal Lyapunov expo-nent (MLE) and dynamic voltage indices at each bus and the whole system. In order to determine the crit-ical contingencies, the values of the indices and the results of the classification of the post-contingency state are statistically analysed. The methodology is tested in the New England 39-bus system, obtaining satisfactory results in relation to the identification not only of the most critical contingencies but also of vulnerable buses to voltage instability. New contri-butions of this work are the contingency classifica-tion methodology, the algorithm for calculating dy-namic indices and the method of classification of the operating state as a function of the STVS problem magnitude.