Abstract: An effective approach for unbalanced three-phase
distribution power flow solutions is proposed in this paper. The
special topological characteristics of distribution networks have been
fully utilized to make the direct solution possible. Two matrices–the
bus-injection to branch-current matrix and the branch-current to busvoltage
matrix– and a simple matrix multiplication are used to
obtain power flow solutions. Due to the distinctive solution
techniques of the proposed method, the time-consuming LU
decomposition and forward/backward substitution of the Jacobian
matrix or admittance matrix required in the traditional power flow
methods are no longer necessary. Therefore, the proposed method is
robust and time-efficient. Test results demonstrate the validity of the
proposed method. The proposed method shows great potential to be
used in distribution automation applications.
Abstract: Newton-Raphson State Estimation method using bus
admittance matrix remains as an efficient and most popular method to
estimate the state variables. Elements of Jacobian matrix are computed
from standard expressions which lack physical significance. In this
paper, elements of the state estimation Jacobian matrix are obtained
considering the power flow measurements in the network elements.
These elements are processed one-by-one and the Jacobian matrix H is
updated suitably in a simple manner. The constructed Jacobian matrix
H is integrated with Weight Least Square method to estimate the state
variables. The suggested procedure is successfully tested on IEEE
standard systems.
Abstract: A considerable progress has been achieved in transient
stability analysis (TSA) with various FACTS controllers. But, all
these controllers are associated with single transmission line. This
paper is intended to discuss a new approach i.e. a multi-line FACTS
controller which is interline power flow controller (IPFC) for TSA of
a multi-machine power system network. A mathematical model of
IPFC, termed as power injection model (PIM) presented and this
model is incorporated in Newton-Raphson (NR) power flow
algorithm. Then, the reduced admittance matrix of a multi-machine
power system network for a three phase fault without and with IPFC
is obtained which is required to draw the machine swing curves. A
general approach based on L-index has also been discussed to find
the best location of IPFC to reduce the proximity to instability of a
power system. Numerical results are carried out on two test systems
namely, 6-bus and 11-bus systems. A program in MATLAB has
been written to plot the variation of generator rotor angle and speed
difference curves without and with IPFC for TSA and also a simple
approach has been presented to evaluate critical clearing time for test
systems. The results obtained without and with IPFC are compared
and discussed.
Abstract: Power flow (PF) study, which is performed to
determine the power system static states (voltage magnitudes and
voltage angles) at each bus to find the steady state operating
condition of a system, is very important and is the most frequently
carried out study by power utilities for power system planning,
operation and control. In this paper, a counterpropagation neural
network (CPNN) is proposed to solve power flow problem under
different loading/contingency conditions for computing bus voltage
magnitudes and angles of the power system. The counterpropagation
network uses a different mapping strategy namely
counterpropagation and provides a practical approach for
implementing a pattern mapping task, since learning is fast in this
network. The composition of the input variables for the proposed
neural network has been selected to emulate the solution process of a
conventional power flow program. The effectiveness of the proposed
CPNN based approach for solving power flow is demonstrated by
computation of bus voltage magnitudes and voltage angles for
different loading conditions and single line-outage contingencies in
IEEE 14-bus system.