Effective monitoring and management applications on modern distribution networks (DNs) require a sound network model and the knowledge of line parameters. Network line impedances are used, among other things, for state estimation and protection relay setting. Phasor measurement units (PMUs) give synchronized voltage and current phasor measurements, referred to a common time reference (coordinated universal time). All synchrophasor measurements can thus be temporally aligned and coordinated across the network. This feature, along with high accuracy and reporting rates, could make PMUs useful for the evaluation of network parameters. However, instrument transformer behavior strongly affects the parameter estimation accuracy. In this paper, a new PMU-based iterative line parameter estimation algorithm for DNs, which includes in the estimation model systematic measurement errors, is presented. This method exploits the simultaneous measurements given by PMUs on different nodes and branches of the network. A complete analysis of uncertainty sources is also performed, allowing the evaluation of estimation uncertainty. Issues related to operating conditions, topology, and measurement uncertainty are thoroughly discussed and referenced to a realistic model of a DN to show how a full network estimator is possible.

Line Impedance Estimation Based on Synchrophasor Measurements for Power Distribution Systems

Pegoraro, Paolo Attilio
Primo
;
Castello, Paolo;Muscas, Carlo
;
2019-01-01

Abstract

Effective monitoring and management applications on modern distribution networks (DNs) require a sound network model and the knowledge of line parameters. Network line impedances are used, among other things, for state estimation and protection relay setting. Phasor measurement units (PMUs) give synchronized voltage and current phasor measurements, referred to a common time reference (coordinated universal time). All synchrophasor measurements can thus be temporally aligned and coordinated across the network. This feature, along with high accuracy and reporting rates, could make PMUs useful for the evaluation of network parameters. However, instrument transformer behavior strongly affects the parameter estimation accuracy. In this paper, a new PMU-based iterative line parameter estimation algorithm for DNs, which includes in the estimation model systematic measurement errors, is presented. This method exploits the simultaneous measurements given by PMUs on different nodes and branches of the network. A complete analysis of uncertainty sources is also performed, allowing the evaluation of estimation uncertainty. Issues related to operating conditions, topology, and measurement uncertainty are thoroughly discussed and referenced to a realistic model of a DN to show how a full network estimator is possible.
2019
Electric network line parameters; Estimation; Measurement uncertainty; phasor measurement unit (PMU); Phasor measurement units; power distribution lines; power system measurements; Time measurement; Transmission line measurements; Uncertainty; voltage and current transducers; Voltage measurement; weighted least square (WLS).; Instrumentation; Electrical and Electronic Engineering
File in questo prodotto:
File Dimensione Formato  
08444098_TIM_param_editoriale.pdf

Solo gestori archivio

Descrizione: versione editoriale
Tipologia: versione editoriale (VoR)
Dimensione 2.16 MB
Formato Adobe PDF
2.16 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
1_IM-18-17197_accepted paper_to_share_withdisclaimer.pdf

accesso aperto

Descrizione: versione accepted post-print per pubblicazione sul sito del docente/ente
Tipologia: versione post-print (AAM)
Dimensione 1.09 MB
Formato Adobe PDF
1.09 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/256702
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 95
  • ???jsp.display-item.citation.isi??? 67
social impact