Abstract: Synchronizing and damping torque coefficients of a synchronous machine can give a quite clear picture for machine behavior during transients. These coefficients are used as a power system transient stability measurement. In this paper, a crow search optimization algorithm is presented and implemented to study the power system stability during transients. The algorithm makes use of the machine responses to perform the stability study in time domain. The problem is formulated as a dynamic estimation problem. An objective function that minimizes the error square in the estimated coefficients is designed. The method is tested using practical system with different study cases. Results are reported and a thorough discussion is presented. The study illustrates that the proposed method can estimate the stability coefficients for the critical stable cases where other methods may fail. The tests proved that the proposed tool is an accurate and reliable tool for estimating the machine coefficients for assessment of power system stability.
Abstract: This paper discusses the performance of critical
trajectory method (CTrj) for power system transient stability analysis
under various loading settings and heavy fault condition. The method
obtains Controlling Unstable Equilibrium Point (CUEP) which is
essential for estimation of power system stability margins. The CUEP
is computed by applying the CTrjto the boundary controlling unstable
equilibrium point (BCU) method. The Proposed method computes a
trajectory on the stability boundary that starts from the exit point and
reaches CUEP under certain assumptions. The robustness and
effectiveness of the method are demonstrated via six power system
models and five loading conditions. As benchmark is used
conventional simulation method whereas the performance is compared
with and BCU Shadowing method.
Abstract: The protection of parallel transmission lines has been a challenging task due to mutual coupling between the adjacent circuits of the line. This paper presents a novel scheme for detection and classification of faults on parallel transmission lines. The proposed approach uses combination of wavelet transform and neural network, to solve the problem. While wavelet transform is a powerful mathematical tool which can be employed as a fast and very effective means of analyzing power system transient signals, artificial neural network has a ability to classify non-linear relationship between measured signals by identifying different patterns of the associated signals. The proposed algorithm consists of time-frequency analysis of fault generated transients using wavelet transform, followed by pattern recognition using artificial neural network to identify the type of the fault. MATLAB/Simulink is used to generate fault signals and verify the correctness of the algorithm. The adaptive discrimination scheme is tested by simulating different types of fault and varying fault resistance, fault location and fault inception time, on a given power system model. The simulation results show that the proposed scheme for fault diagnosis is able to classify all the faults on the parallel transmission line rapidly and correctly.
Abstract: This paper discusses aspects of re-design of loadshedding
schemes with respect to actual developments in the Kosovo
power system. Load-shedding is a type of emergency control that is
designed to ensure system stability by reducing power system load to
match the power generation supply. This paper presents a new
adaptive load-shedding scheme that provides emergency protection
against excess frequency decline, in cases when the Kosovo power
system might be disconnected from the regional transmission
network. The proposed load-shedding scheme uses the local
frequency rate information to adapt the load-shedding pattern to suit
the size and location of the occurring disturbance. The proposed
scheme is tested in a software simulation on a large scale PSS/E
model which represents nine power system areas of Southeast Europe
including the Kosovo power system.
Abstract: This paper proposes transient angle stability
agents to enhance power system stability. The proposed transient
angle stability agents divided into two strategy agents. The
first strategy agent is a prediction agent that will predict power
system instability. According to the prediction agent-s output,
the second strategy agent, which is a control agent, is automatically
calculating the amount of active power reduction that can
stabilize the system and initiating a control action. The control
action considered is turbine fast valving. The proposed strategies
are applied to a realistic power system, the IEEE 50-
generator system. Results show that the proposed technique can
be used on-line for power system instability prediction and control.
Abstract: This paper focuses on PSS/E modeling of wind farms
of Doubly-fed Induction Generator (DFIG) type and their impact on
issues of power system operation. Since Wind Turbine Generators
(WTG) don-t have the same characteristics as synchronous
generators, the appropriate modeling of wind farms is essential for
transmission system operators to analyze the best options of
transmission grid reinforcements as well as to evaluate the wind
power impact on reliability and security of supply. With the high
excepted penetration of wind power into the power system a
simultaneous loss of Wind Farm generation will put at risk power
system security and reliability. Therefore, the main wind grid code
requirements concern the fault ride through capability and frequency
operation range of wind turbines. In case of grid faults wind turbines
have to supply a definite reactive power depending on the
instantaneous voltage and to return quickly to normal operation.