Modeling of the grounding resistance variation using ARMA models

S. Sp Pappas, L. Ekonomou, P. Karampelas, S. K. Katsikas, P. Liatsis

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


This study addresses the problem of modeling the variation of the grounding resistance during the year. An AutoRegressive Moving Average (ARMA) model is fitted (off-line) on the provided actual data using the Corrected Akaike Information Criterion (AICC). The developed model is shown to fit the data in a successful manner. Difficulties occur when the provided data includes noise or errors and also when an on line/adaptive modeling is required. In both cases, and under the assumption that the provided data can be represented by an ARMA model, simultaneous order and parameter estimation of ARMA models under the presence of noise is necessary. In this paper, a new method based on the multi-model partitioning theory which is also applicable to on line/adaptive operation, is used for the solution of the above mentioned problem. The simulations show that the proposed method succeeds in selecting the correct ARMA model order and estimates the parameters accurately in very few steps and even with a small sample size. For validation purposes the method introduced is compared with three other established order selection criteria presenting very good results. The proposed method can be extremely useful in the studies of electrical engineer designers, since the variation of the grounding resistance during the year affects significantly power systems performance and must be definitely considered.

Original languageBritish English
Pages (from-to)560-570
Number of pages11
JournalSimulation Modelling Practice and Theory
Issue number5
StatePublished - May 2008


  • Adaptive multi-model
  • ARMA
  • Filtering
  • Grounding resistance
  • Kalman
  • Order selection
  • Parameter estimation


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