Automatic Identification of Power System Load Models Based on Field Measurements

Research output: Contribution to journalArticlepeer-review

255 Downloads (Pure)

Abstract

With an ever growing complexity, the power grids are designed and operated with an increasingly reduced stability margin. Under such circumstances, the adequate modeling of existing and new power system loads, with all its challenges, is receiving renewed attention. To simplify and to large extent automate the task of load modelling, this paper presents a methodology and associated software tool – Automated Load Modelling Tool (ALMT) to automatically (without human intervention) develop load models and derive corresponding model parameters from recorded power system responses. The approach facilitates automatic identification of load models and derivation of corresponding parameters for three different types of load models, i.e. polynomial, dynamic exponential, and composite load model. Several case studies using real life measurements at 11 kV distribution buses are used to test and validate developed methodology and software tool.
Original languageEnglish
Pages (from-to)3162-3171
Number of pages10
JournalIEEE Transactions on Power Systems
Volume33
Issue number3
Early online date18 Oct 2017
DOIs
Publication statusPublished - May 2018

Keywords

  • load modelling
  • optimisation
  • data filtering
  • power system dynamics

Fingerprint

Dive into the research topics of 'Automatic Identification of Power System Load Models Based on Field Measurements'. Together they form a unique fingerprint.

Cite this