Binary particle swarm optimisation‐based optimal substation coverage algorithm for phasor measurement unit installations in practical systems

Mishra, Chetan; Jones, Kevin D.; Pal, Anamitra; Centeno, Virgilio A.

doi:10.1049/iet-gtd.2015.1077

Binary particle swarm optimisation‐based optimal substation coverage algorithm for phasor measurement unit installations in practical systems

Journal Article · Mon Feb 01 00:00:00 EST 2016 · IET Generation, Transmission, & Distribution

DOI:https://doi.org/10.1049/iet-gtd.2015.1077· OSTI ID:1786871

Mishra, Chetan ^[1]; Jones, Kevin D. ^[2]; Pal, Anamitra ^[3]; Centeno, Virgilio A. ^[1]

Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Blacksburg VA 24061 USA
Virginia Electric and Power Company (d/b/a Dominion Virginia Power) Richmond VA 23219 USA
Network Dynamics and Simulation Science Laboratory Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University Blacksburg VA 24061 USA

Phasor measurement units (PMUs) play an important role in the wide‐area monitoring and protection of modern power systems. Historically, their deployment was limited by the prohibitive cost of the device itself. Therefore, the objective of the conventional optimal PMU placement problem was to find minimum number of devices, which when carefully placed throughout the network, maximised observability subject to different constraints. Due to improvements in relay technology, digital relays can now serve as both relays and PMUs. Under such circumstances, the substation installations consume the largest portion of the deployment cost, and not the devices themselves. Thus, for minimising cost of synchrophasor deployment, number of substation installations must be minimised. This study uses binary particle swarm optimisation to minimise number of substations in which installations must be performed for making all voltage levels observable, while being subject to various practical constraints. Standard IEEE systems have been used to explain the technique. Finally, a large‐scale network of Dominion Virginia Power is used as the test bed for implementation.

View Accepted Manuscript (Publisher)

Sponsoring Organization:: USDOE

Grant/Contract Number:: SC0003957

OSTI ID:: 1786871

Journal Information:: IET Generation, Transmission, & Distribution, Journal Name: IET Generation, Transmission, & Distribution Journal Issue: 2 Vol. 10; ISSN 1751-8687

Publisher:: Institution of Engineering and Technology (IET)Copyright Statement

Country of Publication:: United Kingdom

Language:: English

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