An Efficient Approach for Measurement-Based Composite Load Modeling

Mohammad Rasouli, Reza Sabzehgar, Hamid Reza Teymour

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Measurement-based load modeling, especially in the presence of new loads such as power electronics-interfaced loads and electric vehicles with fast dynamics, requires fast-converging algorithms that provide the model parameters with high reliability. In the current practice, all or only a subset of the parameters of an aggregated load model are estimated using iterative optimization algorithms. Thus, the identification problem either has a high dimension, which leads to a large variance for the estimated parameters, or does not include a subset of the parameters with low sensitivity. In this paper, an efficient approach for the estimation of the composite load model parameters is proposed that addresses these issues. This method partitions the parameters into two subsets; one that appears nonlinearly in the model output, and a second set that affects the outputs linearly. Then, the optimization is performed only with respect to the nonlinear set, with the linear parameters treated as explicit functions of the nonlinear ones. This approach effectively reduces the dimension of the search space since it only includes the nonlinear parameters in the optimization, and also includes the linear parameters by computing them using linear regression at each iteration. These features lead to a much faster convergence while all of the composite load model parameters are estimated reliably. Experimental and simulation data are presented to demonstrate the performance of the proposed method.

Original languageEnglish (US)
Title of host publication2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7310-7314
Number of pages5
ISBN (Electronic)9781479973118
DOIs
Publication statusPublished - Dec 3 2018
Event10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018 - Portland, United States
Duration: Sep 23 2018Sep 27 2018

Publication series

Name2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018

Other

Other10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018
CountryUnited States
CityPortland
Period9/23/189/27/18

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All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management

Cite this

Rasouli, M., Sabzehgar, R., & Teymour, H. R. (2018). An Efficient Approach for Measurement-Based Composite Load Modeling. In 2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018 (pp. 7310-7314). [8558273] (2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ECCE.2018.8558273