Optimum PMU placement for power system state estimation

Israel Akingeneye, Jingxian Wu, Jing Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The integration of phasor measurement units (PMUs) in power grids can greatly enhance the robustness of power grid state estimations. Due to the cost of components and installations, the number of PMUs is usually much less than that of buses in a power system. Therefore one of the critical problems faced by power system design is PMU placement, that is, identifying the buses on which the PMU should be installed. The objective of this paper is to develop PMU placement algorithms to improve the power grid state estimation. Unlike many existing PMU placement algorithms developed based on the concept of critical measurements, we use the estimation mean squared error (MSE) as the design metric. By applying a linear minimum MSE (MMSE) algorithm, the MSE is expressed as an explicit function of the locations of the PMUs. The problem is formulated as a combinatorial optimization problem that is known to be NP-hard. To balance the tradeoff between complexity and performance, we propose two low complexity algorithms, a greedy algorithm that sequentially searches for the best PMU location, and a heuristic ordered MSE algorithm that places PMUs at buses with highest MSE. Simulation results show that the proposed low complexity algorithms can almost achieve the globally optimum performance, and they significantly outperform existing PMU placement algorithms.

Original languageEnglish (US)
Title of host publication2017 IEEE Power and Energy Society General Meeting, PESGM 2017
PublisherIEEE Computer Society
Pages1-5
Number of pages5
ISBN (Electronic)9781538622124
DOIs
StatePublished - Jan 29 2018
Event2017 IEEE Power and Energy Society General Meeting, PESGM 2017 - Chicago, United States
Duration: Jul 16 2017Jul 20 2017

Publication series

NameIEEE Power and Energy Society General Meeting
Volume2018-January
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933

Other

Other2017 IEEE Power and Energy Society General Meeting, PESGM 2017
CountryUnited States
CityChicago
Period7/16/177/20/17

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering

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