Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao IEEE Transactions on...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
IEEE Transactions on Smart Grid
Article . 2019 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
versions View all 1 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

A Fault-Tolerance Based Approach to Optimal PMU Placement

Authors: Saleh Almasabi; Joydeep Mitra;

A Fault-Tolerance Based Approach to Optimal PMU Placement

Abstract

Phasor measurement units (PMUs) have offered significant advancements in power system operation and control. Despite these advantages, the industry has been slow in adopting PMU technology. This slow adoption is partially due to the high cost of installing PMUs, which motivates the optimal PMU placement (OPP) problem. The work presented in this paper is motivated by the idea that the value of a high cost asset can be increased by deploying it to improve network fault-tolerance. This strategy of deploying PMUs in the proximity of higher probability contingencies increases the likelihood of more effective remedial actions, both preventive and corrective. The proposed OPP therefore considers both the cost and the extent to which the PMU placements will benefit system observability in the presence of network vulnerabilities. A bi-level framework is used for optimizing the network vulnerability and the installation cost of PMUs. In the proposed framework, the installation cost of PMUs is treated as the primary objective, and the observability, which incorporates the vulnerability analysis, is treated as the secondary objective. The proposed approach can be used as a multistage installation process or as a single-stage installation process. This approach uses evolutionary algorithms to optimize and prioritize locations and installation cost of the PMUs. The proposed approach is tested on the IEEE 14-bus, IEEE 30-bus, and IEEE reliability test system.

Related Organizations
  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    20
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Top 10%
Top 10%