PMU Optimal Placement in Smart Grid using WLAV Power System Estimator

  • Mohammad Shoaib Shahriar
  • , Yusuf Abubakar Sha'Aban
  • , Ibrahim Omar Habiballah
  • , Farhan Ammar Ahmad

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The monitoring, observation and security of a modern-day smart grid system is highly dependent on the accuracy of the selected state estimator. State estimation provides accurate states of a power system in a real-time frame. The conventional meters, which are mostly installed in current smart grid systems are prone to provide wrong measurements to the estimator, which reduces the efficiency of the state estimation results. Over the last two decades, new and reliable meters have been introduced to electric utilities. For example, phasor measurement units (PMU), which are devices that can provide voltage and current phasors with a very high accuracy are readily available. However, they are expensive and need to be optimally placed on the smart grids. This paper presents a technique for optimizing the placement of PMUs, with the objective of improving the estimation performance using Genetic Algorithm (GA). The weighted least absolute value (WLAV) estimator, which is one of the well-established robust estimators, is being selected for simulation. The IEEE-14 and 30-bus power systems are chosen to demonstrate the effectiveness of proposed optimal PMU placement.

Original languageEnglish
Title of host publication2019 2nd International Conference of the IEEE Nigeria Computer Chapter, NigeriaComputConf 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728107134
DOIs
StatePublished - Oct 2019

Publication series

Name2019 2nd International Conference of the IEEE Nigeria Computer Chapter, NigeriaComputConf 2019

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Genetic Algorithm
  • Optimal PMU Placement
  • Phasor Measurement Unit
  • State Estimation
  • Weighted Least Absolute Value

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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