Visible to the public Optimal placement of Phasor Measurement Units in power grids using Memetic Algorithms

TitleOptimal placement of Phasor Measurement Units in power grids using Memetic Algorithms
Publication TypeConference Paper
Year of Publication2014
AuthorsLinda, O., Wijayasekara, D., Manic, M., McQueen, M.
Conference NameIndustrial Electronics (ISIE), 2014 IEEE 23rd International Symposium on
Date PublishedJune
Keywordsdistribution networks, genetic algorithms, hill-climbing method, Idaho region power network, IEEE benchmark power networks, Memetic Algorithm, memetic algorithms, Memetics, Observability, OPP problem, Optimal PMU Placement, phasor measurement, phasor measurement units, power buses, power grid, power grids, power network systems control, power network systems protection, power system control, Power system protection, power system reliability, power system security, situational awareness, Smart grid, smart power grids, Sociology, Statistics, synchronized measurement technology, wide area monitoring
Abstract

Wide area monitoring, protection and control for power network systems are one of the fundamental components of the smart grid concept. Synchronized measurement technology such as the Phasor Measurement Units (PMUs) will play a major role in implementing these components and they have the potential to provide reliable and secure full system observability. The problem of Optimal Placement of PMUs (OPP) consists of locating a minimal set of power buses where the PMUs must be placed in order to provide full system observability. In this paper a novel solution to the OPP problem using a Memetic Algorithm (MA) is proposed. The implemented MA combines the global optimization power of genetic algorithms with local solution tuning using the hill-climbing method. The performance of the proposed approach was demonstrated on IEEE benchmark power networks as well as on a segment of the Idaho region power network. It was shown that the proposed solution using a MA features significantly faster convergence rate towards the optimum solution.

URLhttp://ieeexplore.ieee.org/document/6864930/
DOI10.1109/ISIE.2014.6864930
Citation Key6864930