Location

Hilton Waikoloa Village, Hawaii

Event Website

http://www.hicss.hawaii.edu

Start Date

1-4-2017

End Date

1-7-2017

Description

An accurate dynamic load model plays a crucial role in the analysis of power system transient stability. The WECC dynamic composite load model (CMPLDW) has been developed recently to better represent fault-induced delayed-voltage-recovery (FIDVR) events, which are of increasing concern to electric utilities. To facilitate the understanding of the CMPLDW, it is worth studying the effect of parameters that describe the model structure on its dynamic response. In this paper, we show that 1) some parameters have very minimal sensitivities under certain FIDVR events; 2) sensitivities of certain parameters are strongly dependent on the temporal profile of given fault, such as its minimum fault voltage or recovery time; and 3) some parameters share similar sensitivity patterns and thus the change of their values may complement each other. These observations are essential for further developing enhanced measurement-based dynamic load modeling approaches by tackling the parameter identifiability issues pointed out in the present work.

Share

COinS
 
Jan 4th, 12:00 AM Jan 7th, 12:00 AM

Parameter Sensitivity and Dependency Analysis for the WECC Dynamic Composite Load Model

Hilton Waikoloa Village, Hawaii

An accurate dynamic load model plays a crucial role in the analysis of power system transient stability. The WECC dynamic composite load model (CMPLDW) has been developed recently to better represent fault-induced delayed-voltage-recovery (FIDVR) events, which are of increasing concern to electric utilities. To facilitate the understanding of the CMPLDW, it is worth studying the effect of parameters that describe the model structure on its dynamic response. In this paper, we show that 1) some parameters have very minimal sensitivities under certain FIDVR events; 2) sensitivities of certain parameters are strongly dependent on the temporal profile of given fault, such as its minimum fault voltage or recovery time; and 3) some parameters share similar sensitivity patterns and thus the change of their values may complement each other. These observations are essential for further developing enhanced measurement-based dynamic load modeling approaches by tackling the parameter identifiability issues pointed out in the present work.

http://aisel.aisnet.org/hicss-50/es/monitoring/6