الفهرس 
PHASOR MEASUREMENT UNIT PLACEMENT AND TREE SEARCH METHODOnly 14 pages are availabe for public view
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Abstract
Phasor Measurement Unit (PMU) is considered to be one of the most
important and advanced measuring devices in modem power systems. The
distinction comes from its unique ability to provide synchronized phasor
measurements of voltages and currents from widely dispersed locations in an
electric power grid. PMUs are operated under control and monitoring of the
Global Positioning System (GPS) with accuracy of timing pulses in the order of
I microsecond, which leads to the same accuracy for the PMUs synchronized
readings. PMUs revolutionize the way power systems are monitored and
controlled. This revolution can add to Wide Area Monitoring System (W AMS)
technology. However, it is not economical to spread the PMUs allover the bus
bars of the power system. Also in some power systems, there are buses with
deficiency in communication facility. So there is a great need for optimal PMUs’
allocation. Particle Swarm Optimization (PSO) is a stochastic, population-based
evolutionary algorithm for problem solving. It is a kind of swarm intelligence
that is based on social-psychological principles. It is a powerful method for a
continuous definition domain. Discrete PSO (DPSO) is an adapted PSO
algorithm for solving discrete optimization problems. Optimal allocation of
PMUs leads to more efficient utilization of PMUs’ outputs in power system
appl ications.
State estimation plays a great and important role in the monitoring and
control of power systems. It is the process of determin ing a value to an unknown
system state variable based on measurements from the system according to some
criteria. The aim of state estimation is to obtain the best possible values of the
bus voltage magn itudes and relative phase angles at the system nodes by processing the available network data. Correlating PM Us location to state
estimation is very important for power system monitoring and control.
Voltage instability is one of the very important power system issues. It can
be responsible for several major network collapses. Voltage stability monitoring
is one of the fields in which the readings of PMUs can be utilized. Voltage
magnitude, real power and reactive power are conventionally used for voltage
stability monitoring.
In this research, a new modified DPSO technique is developed to
determine the optimal number and locations for PMUs in power system network
for different depths of unobservability. The phascrs readings of PMUs are taken
into consideration in a new hybrid parameters state estimation analysis to
achieve a higher. degree of accuracy of the solution. The effect of changing the
locations and numbers of PMUs through the- buses of the power network on the
system state estimation is also studied with a new methodology. The new
method is achieved by moving one PMU over all the network buses till fixing
the location of PMU on the bus with the minimum state estimation residual error.
Another PMU is moved, by the same way, over the remaining network buses- till
the optimal number and locations of PMUs with least minimum residual error is
found.
The readings of the allocated PMUs are to be utilized using a newly
developed technique for on-line voltage instability alarming predictor. The
predictor gives two types of alarms, one for voltage lim it violation (10% voltage
decrease) and the other for voltage collapse prediction. Both alarms are issued
according to the maximum permissible angle difference between bus voltages for
certain bus loading angle. The time taken by the alarming predictor is very small,
and is determined by the speed of PM Us and the used computational system.