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: The phase compensation method was proposed based on the concept of the damping torque analysis (DTA). It is a method for the design of a PSS (power system stabilizer) to suppress local-mode power oscillations in a single-machine infinite-bus power system. This paper presents the application of the phase compensation method for the design of a PSS in a multi-machine power system. The application is achieved by examining the direct damping contribution of the stabilizer to the power oscillations. By using linearized equal area criterion, a theoretical proof to the application for the PSS design is presented. Hence PSS design in the paper is an example of stable tending control by localized method.
Abstract: The growth in the demand of electrical energy is
leading to load on the Power system which increases the occurrence
of frequent oscillations in the system. The reason for the oscillations
is due to the lack of damping torque which is required to dominate
the disturbances of Power system. By using FACT devices, such as
Unified Power Flow Controller (UPFC) can control power flow,
reduce sub-synchronous resonances and increase transient stability.
Hence, UPFC is used to damp the oscillations occurred in Power
system. This research focuses on adapting the neuro fuzzy controller
for the UPFC design by connecting the infinite bus (SMIB - Single
machine Infinite Bus) to a linearized model of synchronous machine
(Heffron-Phillips) in the power system. This model gains the
capability to improve the transient stability and to damp the
oscillations of the system.
Abstract: In this paper, investigation of subsynchronous
resonance (SSR) characteristics of a hybrid series compensated
system and the design of voltage controller for three level 24-pulse
Voltage Source Converter based Static Synchronous Series
Compensator (SSSC) is presented. Hybrid compensation consists of
series fixed capacitor and SSSC which is a active series FACTS
controller. The design of voltage controller for SSSC is based on
damping torque analysis, and Genetic Algorithm (GA) is adopted for
tuning the controller parameters. The SSR Characteristics of SSSC
with constant reactive voltage control modes has been investigated.
The results show that the constant reactive voltage control of SSSC
has the effect of reducing the electrical resonance frequency, which
detunes the SSR.The analysis of SSR with SSSC is carried out based
on frequency domain method, eigenvalue analysis and transient
simulation. While the eigenvalue and damping torque analysis are
based on D-Q model of SSSC, the transient simulation considers both
D-Q and detailed three phase nonlinear system model using
switching functions.
Abstract: This paper presents Simulation and experimental
study aimed at investigating the effectiveness of an adaptive artificial
neural network stabilizer on enhancing the damping torque of a
synchronous generator. For this purpose, a power system comprising
a synchronous generator feeding a large power system through a
short tie line is considered. The proposed adaptive neuro-control
system consists of two multi-layered feed forward neural networks,
which work as a plant model identifier and a controller. It generates
supplementary control signals to be utilized by conventional
controllers. The details of the interfacing circuits, sensors and
transducers, which have been designed and built for use in tests, are
presented. The synchronous generator is tested to investigate the
effect of tuning a Power System Stabilizer (PSS) on its dynamic
stability. The obtained simulation and experimental results verify the
basic theoretical concepts.