Open AccessDynamic equivalencing of an active distribution network for large‐scale power system frequency stability studies
Author(s) -
Golpîra Hêmin,
Seifi Hossein,
Haghifam Mahmoud Reza
Publication year - 2015
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.2015.0484
Subject(s) - robustness (evolution) , control theory (sociology) , cluster analysis , sensitivity (control systems) , computer science , ac power , stability (learning theory) , electric power system , operating point , power (physics) , mathematics , engineering , electronic engineering , control (management) , physics , quantum mechanics , machine learning , biochemistry , chemistry , artificial intelligence , gene
This study presents an approach for developing the dynamic equivalent model of an active distribution network (ADN), consisting of several micro‐grids, for frequency stability studies. The proposed grey‐box equivalent model relies on Prony analysis to establish stop time and load damping as the required modelling parameters. Support vector clustering (SVC) and grouping procedure are employed for aggregation and order‐reduction of ADN. This significantly decreases the sensitivity of the estimated parameters to operating point changes which, in turn, guarantees the model robustness. This is done through representing the SVC output, that is, clusters, by cluster substitutes. The final ADN dynamic equivalent model is represented by several groups, in which their mutual interactions are taken into account by a new developed mathematical‐based criterion. Simulation results reveal that the proposed model is robust which could successfully take into account the continuous and discontinuous uncertainties.