Open AccessPredictive auto‐reclosure approach to enhance transient stability of grid‐connected DGs
Author(s) -
Abedini Moein,
SanayePasand Majid,
Davarpanah Mahdi,
Lesani Hamid,
Shahidehpour Mohammad
Publication year - 2019
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.2018.6455
Subject(s) - transient (computer programming) , circuit breaker , control theory (sociology) , engineering , fault (geology) , stability (learning theory) , margin (machine learning) , generator (circuit theory) , grid , computer science , power (physics) , mathematics , electrical engineering , artificial intelligence , geology , operating system , physics , geometry , control (management) , quantum mechanics , machine learning , seismology
This study introduces a predictive auto‐reclosure scheme based on faster‐than‐real‐time (FTRT) analysis for synchronous generator type of distributed generation (DG) units to decrease DG oscillations after successful reclosure and also enhance transient stability margin of the unit after unsuccessful reclosure. The FTRT analysis, as a new concept for the protective relaying, represents a powerful predictive auto‐reclosure scheme which is based on a state‐space model of the DG unit. After a fault scenario and the first operation of the associated breaker, the FTRT analysis predicts energy level of the DG unit and determines an optimum dead‐time corresponding to the minimum energy level of the DG unit for reclosure that can provide an appropriate margin for transient stability. The effectiveness and accuracy of the proposed method are verified based on a test system. The results confirm that the proposed approach can effectively enhance transient stability for unsuccessful reclosure and reduce the corresponding oscillations after reclosure.