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: 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.