The is formulated as an optimization problem where

ever-growing global population as well as the consumption of electricity, has
triggered the increasing demand for reliable electricity. To prevent events
such as loss of electricity, power network providers must recognizes the
quality and stability of various parts of transmission network through
monitoring and measuring equipment. Based on the GPS synchronized clock, the phasor
measurement unit can measure a vast amount of critical power network
information, which includes bus voltage, bus current, generator speed and power
angle.   A decision Model for the
Optimal Placement of Phasor Measurement Units the in the power transmission
system to provide a two phase network observability of voltage and current
measurement. The single phase PMU installations are used in some applications,
because of cost and availability of signals (1). By
receiving the real-time PMU measurement information over wide locations, the
operators in the central control room can monitor and analyze the quality of
the distribution network under static and dynamic operating conditions. To
reduce the maintenance fee and unit costs, optimal PMU placement (OPP) is
implemented to minimize the amount of PMUs installed and to achieve the entire
degree of observability. As a result, the problem of optimal PMU placement has
been focused on as a new angle of research interest in the power network in
recent years.

              The smart
grid applications and their infrastructure with PMU installations in all
substations can significantly improve the reliability of power network (2). Since PMUs are expensive, their procurement and
installation needs to be planned both in terms of economy and utility. This
method aims at finding the minimal set of PMUs which ensures full observability
of the system network. Thus the problem of optimal placement of PMUs is
formulated as an optimization problem where the number of PMUs is
minimized subject to complete system observability. Various optimization tool
to determine the installation of minimum number of PMUs to make the power
system observable. It also includes extension for single line outages (3).  Several optimization algorithms are reported
to have been used to address optimal PMUs placement and they all aim at placing
minimum number of PMUs at strategic buses within the network. A few such
algorithms reviewed are Binary particle Swarm algorithm, Immunity Genetic
Algorithm, Binary search Algorithm, and the Integer Linear Programming (ILP)
Algorithm.                                   Each algorithm has its strengths
and disadvantages which are related to logic behind its optimization approach.
With PMUs as the main resource and reason for this study, it would be
worthwhile effort to develop method for optimal placement of PMUs with this
purpose in mind. The strategy of PMU placement can be designed around
minimizing the overall system electrical distance from PMUs. A optimal algorithm
for scheduling Phasor Data Transmissions in Smart Grid Networks considering
number of PMU placement and its redundancy level for obtaining full
observability was explained in this reference(4).

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