Biblio

In operation centers, it is important to know the power transfer limit to guarantee the safety operation of the power system. The Voltage Stability Margin (VSM) is a widely used measure and needs to definition of a load growth direction (LGD) to be computed. However, different definitions of LGD can provide different VSMs and then the VSM may not be reliable. Besides, the measure of this power transfer limit usually is related to the Saddle-Node Bifurcation. In dynamic security assessment (DSA) is highly desirable to identify limit regions where the power system can operate safely due to Hopf (HB) and Saddle-Node (SNB) Bifurcations. This paper presents a modeling of the power system incorporating the LGD variation based on participation factors to evaluate the effects on the stability margin estimation due to HB and SNB. A direct method is used to calculate the stability margin of the power system for a given load direction. The analysis was performed in the IEEE 39 bus system.

In interconnected power systems, dynamic model reduction can be applied to generators outside the area of interest (i.e., study area) to reduce the computational cost associated with transient stability studies. This paper presents a method of deriving the reduced dynamic model of the external area based on dynamic response measurements. The method consists of three steps, namely dynamic-feature extraction, attribution, and reconstruction (DEAR). In this method, a feature extraction technique, such as singular value decomposition (SVD), is applied to the measured generator dynamics after a disturbance. Characteristic generators are then identified in the feature attribution step for matching the extracted dynamic features with the highest similarity, forming a suboptimal “basis” of system dynamics. In the reconstruction step, generator state variables such as rotor angles and voltage magnitudes are approximated with a linear combination of the characteristic generators, resulting in a quasi-nonlinear reduced model of the original system. The network model is unchanged in the DEAR method. Tests on several IEEE standard systems show that the proposed method yields better reduction ratio and response errors than the traditional coherency based reduction methods.