DocumentCode :
2535816
Title :
Load model parameter derivation using an automated algorithm and measured data
Author :
Maitra, A. ; Gaikwad, A. ; Pourbeik, P. ; Brooks, D.
Author_Institution :
Syst. Studies Group, EPRI, Knoxvulle, TN
fYear :
2008
fDate :
20-24 July 2008
Firstpage :
1
Lastpage :
7
Abstract :
This paper summaries some of the key results achieved in the second phase of a multi-year collaborative load modeling research project. After having identified suitable types of load monitoring devices, actual field data for load model development and validation were collected at appropriate locations for several months to more than a year in three different utilities. This data was post-processed using an automated methodology to filter out events suitable for load model parameter estimation. Two load model structures were then used with an automated parameter estimation algorithm to fit model parameters using the field data collected. The models thus developed were then validated using Siemens PTI PSS/ETM dynamic simulation program. This whole process resulted in some key insights and valuable conclusions for future load modeling research efforts.
Keywords :
power system identification; ETM dynamic simulation program; Siemens PTI PSS; automated algorithm; load model parameter derivation; load model parameter estimation; load monitoring devices; Impedance; Induction motors; Load modeling; Parameter estimation; Phase measurement; Power measurement; Power system modeling; Reactive power; Signal processing algorithms; Voltage; dynamic models; identification techniques; load modeling; measurement; static models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE
Conference_Location :
Pittsburgh, PA
ISSN :
1932-5517
Print_ISBN :
978-1-4244-1905-0
Electronic_ISBN :
1932-5517
Type :
conf
DOI :
10.1109/PES.2008.4596333
Filename :
4596333
Link To Document :
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