09-07-2013, 04:16 PM
STUDY OF THE UTILIZATION AND BENEFITS OF PHASOR MEASUREMENT
UNITS FOR LARGE SCALE POWER SYSTEM STATE ESTIMATION
STUDY OF THE UTILIZATION.pdf (Size: 974.68 KB / Downloads: 60)
ABSTRACT
This thesis will investigate the impact of the use of the Phasor Measurement Units
(PMU) on the state estimation problem. First, incorporation of the PMU measurements in a
conventional state estimation program will be discussed. Then, the effect of adding PMU
measurements on the state estimation solution accuracy will be studied. Bad data
processing in the presence of PMU measurements will also be presented. Finally, a multiarea
state estimation method will be developed. This method involves a two level
estimation scheme, where the first level estimation is carried out by each area
independently. The second level estimation is required in order to coordinate the solutions
obtained by each area and also to detect and identify errors in the boundary measurements.
The first objective of this thesis is to formulate the full weighted least square state
estimation method using PMUs. The second objective is to derive the linear formulation of
the state estimation problem when using only PMUs. The final objective is to formulate a
two level multi-area state estimation scheme and illlustrate its performance via simulation
examples.
INTRODUCTION
Modern Power System Operations
Over the twenty years, electric power industry in many countries has been undergoing
fundamental changes due to the process of deregulation [1]-[4]. The belief is that
competitive markets will lead to more efficient power generation, more technological
innovations, and eventually to lower retail prices. In an interconnected system, there are
multiple companies who must cooperate to run the system. Some companies may be
reluctant to exchange their data for security concerns. In addition, the power system
network is growing larger and more complex shared by more providers after the
deregulation.
In this situation, the function of state estimation is becoming more important, because
it is the primary tool for monitoring and control based on the real-time data received from
the measurement units. As an example, one of the causes of Northeast blackout of 2003
was the poor control-room procedures and failure of power-grid organization to keep it
from spreading [5]. The security analysis, economic dispatch, etc. strongly depend on the
accuracy of data provided by the state estimation.
Thesis Contributions
One of the contributions of this thesis is that it shows the effect of PMUs on the
accuracy of variables. After showing how to implement the PMU measurement in state
estimation, the effect is discussed by gradually increasing the PMU numbers. Four different
kinds of IEEE Bus Systems are tested. Interesting thing is that the improved accuracy of
variables are somewhat saturated when PMUs are implemented at nearly 10% of the total
system buses. Second contribution of this thesis is the introduction of the linear formulated
state estimation. There’s no need to update the Jacobian matrix in state estimation
algorithm when using only PMU measured data.
Organization of This Thesis
This thesis is composed of 6 chapters. Chapter I is the introduction. It shows the
current problems and reviews the problem of state estimation. Chapter II presents the
specific modeling and simulation method of the full weighted least square state estimation.
Chapter III is the introduction of the linear formulation of the state estimation problem
when using PMUs. Simulation works and bad data processing with the linear formulation
are illustrated. Chapter IV shows the benefits of using PMUs. Improved accuracy of the
estimated variables with PMUs is illustrated. Chapter V shows a multi-area state estimation
method with PMUs. Firstly, current method of multi-area state estimation is reviewed, and
proposed method is described. Then, the simulation results of the proposed multi-area state
estimation method described. Finally, Chapter VI contains conclusions about this thesis and
future work to make the state estimation method more applicable for real systems.
Observability and Bad Data Detection
If the entire state vector of bus voltage magnitudes and angles can be estimated from
the set of available measurements, the power system with the specified measurement set is
said to be observable. However, some measurement failures may occur in the power system
at anytime. In this situation, the power system state estimator can not estimate bus voltage
magnitudes and angles at all buses. It can only estimate a portion of the entire network. If a
limited number of measurement units are exist, then the units should be placed properly to
make the entire system observable. Observability and measurement placement problems are
well described in [24]-[27]. Other than these problems, the method of bad data detection is
also studied in this thesis.
Conclusions
In chapter II the way of incorporating the PMU data to the conventional measurement
set is discussed. A PMU can measure voltage and current with magnitude and phasors. The
current measurement is implemented to the measurement set as a rectangular form.
Equations for the added measurements are illustrated in detail including the elements of the
Jacobian matrix. It is expected that those PMU measured data improve the measurement
redundancy and accuracy, due to the small error standard deviations of PMU.
A linear formulation of the state estimation is investigated in chapter III, using only
PMU measured data. All the variables and measurements are reformed as a rectangular
form, and they are treated separately during the estimation process. This linear formulation
of the PMU data can produce the estimation result by a single calculation not requiring any
iterations. Several examples are tested including bad data detection case. If a mesaurement
set having only PMU data is exist in the real world, the improvement of the computation
time and accuracy is expected, with the linear formulation of the state estimation.