Modeling of the behavior power flow on transmission lines based on voltage and current synchronopasors

Alex Sanchez, Diego Carrion

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This work presents a methodology to determine the behavior of the power through the networks of the Electric Power Systems (SEP) based on the load behavior that can be characterized by the static model ZIP, which has components of constant impedance, constant current and constant power, which are estimated by the method of least squares that are considered as a problem of nonlinear optimization (NLP). The problem approach begins with the location of phasor measurement units (PMUs) within the SEP, posing an optimization problem that is solved by mixed linear programming (MILP) subject to observability constraints. Then an AC power flow is proposed which is solved by the Newton Raphson approximation algorithm to determine the initial operating conditions in the bars where the PMUs are to be installed. Finally, the problem of optimization with least squares is proposed to estimate the coefficients of impedance, current and constant power, which together with the synchrophasor data presented by the PMUs allow to characterize the load in the installation bars and through the characteristics of the load I was able to study the behavior of the power flow through the SEP networks. As a practical case, this methodology is developed in the 9-bar system of the IEEE.

Translated title of the contributionModelado del comportamiento del flujo de potencia en líneas de transmisión basado en sincronopasores de tensión y corriente
Original languageEnglish
Pages (from-to)1142-1149
Number of pages8
JournalIEEE Latin America Transactions
Volume16
Issue number4
DOIs
StatePublished - 1 Apr 2018

Keywords

  • Load characterization
  • PMUs
  • ZIP model

Fingerprint

Dive into the research topics of 'Modeling of the behavior power flow on transmission lines based on voltage and current synchronopasors'. Together they form a unique fingerprint.

Cite this