Title

Characterization of voltage dips and swells in a DG embedded distribution network during and subsequent to islanding process and grid re-connection

RIS ID

125015

Publication Details

M. R. Alam, K. M. Muttaqi & A. Bouzerdoum, "Characterization of voltage dips and swells in a DG embedded distribution network during and subsequent to islanding process and grid re-connection," in 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017, 2017, pp. 1-9.

Abstract

Stand-alone operation of distributed generations (DGs) under islanded mode is achieved by appropriate switching of controllers from grid-parallel to stand-alone mode. Conversely, during grid-restoration, reverse switching operation is employed. These operations cause voltage quality issues; among these issues, voltage dips and swells are two crucial events which are encountered during and subsequent to islanding. This paper characterizes the voltage dips and/or swells caused by the islanding of DG and its subsequent pre- And post-islanding events. Pre-islanding events encompass the fault initiated islanding scenarios, whereas post-islanding events are associated with transitional state, island stabilization and grid-reconnection states. Considering pre- And post-islanding scenarios, this paper classifies and characterizes the voltage dips and swells using an algorithm incorporating three-phase voltage ellipse and 3D polarization ellipse parameters. Three-phase voltage ellipse parameters, namely, major axis, minor axis and inclination angle of ellipse, are exploited for characterization and classification of voltage dips/swells based on their affected phases, whereas 3D polarization ellipse parameters are employed for classifying seven dip-types, namely A, B, D, F, E, C, and G. Islanding and its subsequent scenarios are simulated using a test distribution network of Australia embedded with DG, and the voltage dips and swells are characterized using the proposed algorithm.

Please refer to publisher version or contact your library.

Share

COinS
 

Link to publisher version (DOI)

http://dx.doi.org/10.1109/IAS.2017.8101864