Optimal Phasor Measurement Units Placement in Radial Distribution Networks Using Integer Linear Programming

dc.contributor.authorTangi, S.
dc.contributor.authorGaonkar, D.N.
dc.date.accessioned2026-02-08T16:50:22Z
dc.date.issued2021
dc.description.abstractThe traditional passive distribution networks are evolving into active distribution networks with the integration of dispersed generation (DG) to distribution networks. The conventional network monitoring systems do not monitor and provide the information accurately at a faster rate due to the intermittency nature of sources such as wind and solar. Hence, a real-time accurate and faster monitoring equipment like phasor measurement unit (PMU) is needed. The focal objective of this work is to bring the power distribution network more closely aligned with the smart grid communication technology for better system monitoring conditions. This paper presents the deployment of PMU optimal allocation in the radial distribution network by adopting an integer linear programming (ILP) technique for the system’s full observability at a standard operating condition. Standard radial test feeders such as 12-bus, 15-bus, 28-bus, IEEE 33-bus, IEEE 69-bus, and 119-bus are chosen to study the effect of PMU placement problem. MATLAB programming is used as a simulation software to check the observability of the above test systems. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
dc.identifier.citationLecture Notes on Data Engineering and Communications Technologies, 2021, Vol.58, , p. 1021-1031
dc.identifier.issn23674512
dc.identifier.urihttps://doi.org/10.1007/s41060-025-00823-x
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/33757
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.subjectCommunication
dc.subjectInteger linear programming
dc.subjectOptimal placement problem
dc.subjectPhasor measurement unit
dc.subjectSmart grid
dc.titleOptimal Phasor Measurement Units Placement in Radial Distribution Networks Using Integer Linear Programming

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