Identification of topology changes in power grids using phasor measurements

Journal Article · Mon Nov 17 00:00:00 EST 2014 · Applied Stochastic Models in Business and Industry

DOI:https://doi.org/10.1002/asmb.2082· OSTI ID:1401593

Wiel, Scott Vander ^[1]; Bent, Russell ^[2]; Casleton, Emily ^[3]; Lawrence, Earl ^[2]

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1. Statistical Sciences Group Los Alamos National Laboratory Los Alamos NM U.S.A.
2. Energy and Infrastructure Analysis Los Alamos National Laboratory Los Alamos NM U.S.A.
3. Statistical Sciences Group Los Alamos National Laboratory Los Alamos NM U.S.A., Department of Statistics Iowa State University Ames IA U.S.A.

Phasor measurement units (PMUs) are increasingly important for monitoring the state of an electrical power grid and quickly detecting topology changes caused by events such as lines going down or large loads being dropped. Phasors are complex‐valued measurements of voltage and current at various points of generation and consumption. If a line goes down or a load is removed, power flows change throughout the grid according to known physical laws, and the probability distribution of phasor measurements changes accordingly. This paper develops a method to estimate the current topology of a power grid from phasor measurements and considers the design goal of placing PMUs at strategic points in a distribution system to achieve good sensitivity to single‐line outages. From a vector of phasor measurements, probabilities are computed corresponding to the scenario that all power lines are operational and to alternate scenarios in which each line goes down individually. These probabilities are functions of the joint distributions of phasor measurements under each possible scenario, obtained through Monte Carlo simulations with random load profiles. We use log‐spline densities to estimate marginal distributions of phasor measurements and fold these into a multivariate Gaussian copula to capture important correlations. Sensitivity to outages varies according to which line goes down and where PMUs are placed on the grid. A greedy search algorithm is demonstrated for placing PMUs at locations that provide good sensitivity to single‐line outages. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

• Sponsoring Organization: USDOE
• OSTI ID: 1401593
• Journal Information: Applied Stochastic Models in Business and Industry, Journal Name: Applied Stochastic Models in Business and Industry Vol. 30 Journal Issue: 6; ISSN 1524-1904
• Publisher: Wiley Blackwell (John Wiley & Sons)
• Country of Publication: United Kingdom
• Language: English