Reducing Identified Parameters of Measurement-Based Composite Load Model

Ma, J., Han, D., He, R., Dong, Z.Y. and Hill, D.J. (2008) Reducing Identified Parameters of Measurement-Based Composite Load Model. IEEE Transactions on Power Systems, 23 1: 76-83. doi:10.1109/TPWRS.2007.913206

Author Ma, J.
Han, D.
He, R.
Dong, Z.Y.
Hill, D.J.
Title Reducing Identified Parameters of Measurement-Based Composite Load Model
Journal name IEEE Transactions on Power Systems   Check publisher's open access policy
ISSN 0885-8950
Publication date 2008-02-01
Year available 2008
Sub-type Article (original research)
DOI 10.1109/TPWRS.2007.913206
Open Access Status Not yet assessed
Volume 23
Issue 1
Start page 76
End page 83
Total pages 8
Editor Vittal, V.
Place of publication USA
Publisher IEEE
Language eng
Subject C1
850699 Energy Storage, Distribution and Supply not elsewhere classified
090607 Power and Energy Systems Engineering (excl. Renewable Power)
Abstract A load model is one of the most important elements in power system simulation and control. Recently, the constant impedance, constant current, and constant power load in combination with the induction motor load have been widely used as the composite load model, whose parameters are all identified from the field measurements in measurement-based load modeling practices so far. However, there is virtually no research conducted on whether all these parameters could really be identified. This paper investigates the possibility on reducing the number of composite load model parameters to be identified from field measurements. This paper first shows that direct application of the IEEE load motor parameters in the composite load model may be inadequate on describing the load dynamics over different operating status. Then the perturbation method is used to derive the trajectory sensitivities of the equivalent motor parameters, based on which the reduction on the identified parameters of the composite load model is presented. Two cases of measurement-based load modeling in North China and Northeast China are studied to illustrate the validity of the reduction method. It is shown that the reduction does not lose the model's capability on describing the load dynamics. The reduction on the number of identified parameters not only provides a possible way to solve the multi-valued load model problem based on the current practices on measurement-based load modeling, but it also facilitates building of the load model with more components included in it. Meanwhile, reducing the identified parameters reduces the identification time; thus, the proposed strategy significantly enhances the efficiency of the load modeling work.
Keyword Composite load model
Field measurements
Power system stability
Trajectory sensitivity
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

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