Discrete Empirical Interpolation Method Based Dynamic Load Model Reduction

Nan Duan, Junbo Zhao, Xiao Chen, Bin Wang, Song Wang

Research output: Contribution to conferencePaper

1 Scopus Citations


Dynamic load models add significant complexity to bulk power system time-domain simulations. The complexity is due to the large number of ordinary differential equations (ODEs) introduced by the dynamic load components such as induction motors. It is challenging to derive reduced-order models (ROMs) for dynamic loads due to the nonlinear functions in their governing equations. This paper applies the discrete empirical interpolation method enhanced proper orthogonal decomposition (DEIM-POD) to approximate the full dynamic load model with the ROM that minimizes the projection error of the nonlinear functions in dynamic load ODEs onto their dominant modes. This approach only requires evaluation of nonlinear functions at selected observation points. The observation points selected by DEIM also provide information for screening critical load buses where dynamic load model parameters contribute the most to the accuracy of ROM across multiple contingencies. The proposed approach is validated on IEEE 9-bus, WECC 179-bus and 2384-bus Polish systems.
Original languageAmerican English
Number of pages5
StatePublished - 2021
Event2021 IEEE Power & Energy Society General Meeting (PESGM) - Washington, D.C.
Duration: 26 Jul 202129 Jul 2021


Conference2021 IEEE Power & Energy Society General Meeting (PESGM)
CityWashington, D.C.

NREL Publication Number

  • NREL/CP-5D00-78356


  • bulk power system
  • dynamic load model
  • nonlinear function
  • ordinary differential equation
  • reduced-order model
  • time-domain simulation


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