Trajectory sensitivity based identification of synchronous generator and excitation system parameters

Abstract

A b s t r a c t ____ -T h i s p a p e r d e s c r i b e s t h e a p p l i c a t i o n of a t r a j e c t o r y s e n s i t i v i t y method t o t h e i d e n t i f i c a t i o n ofsynchronous g e n e r a t o r r e a c t a n c e s a n d e x c i t a t i o n s y s t c m

Multi-parameter trajectory sensitivity approach for location of series-connected controllers to enhance power system transient stability

“…This statement is confirmed by results shown in Fig. 7 which correspond to the relative rotor angle trajectory of the generator connected at node 38, ı 38-39 , for cases without compensation, and 30% of capacitive compensation at the most sensitive lines B 26-29 and B [25][26] . For the three cases, the fault occurs on line 26-28, near node 28, and is cleared at 166 ms by tripping the line.…”

“…In addition, the analytical formulation of this approach overcomes the need of repetitive simulations to judge how changes in operating conditions influence the system stability. Applications of TS include the study of parameter uncertainty in system behavior [24,25], determination of well-conditioned parameters for reliable estimation [26][27][28], and determination of critical machines which are likely to go unstable for a given loading condition and a specified contingency [29], among others [30].…”

A hybrid method for the dynamic parameter identification of generators via on-line measurements

“…There are two typical approaches for dynamic parameter identification: field test [1][2] and on-line measurements [3][4][5][6][7]. Field test is a good means to gain direct insight for dynamic parameters.…”

“…Protection equipments and some newly developed Intelligent Electric Devices (IED) such as Phasor Measurement Units (PMU) can provide the parameter identification required information with better resolution and time synchronization among measured dynamic data. Several researchers have focused on parameter identification via online measurements [3][4][5][6][7].…”

Estimating dynamic model parameters for adaptive protection and control in power system

“…The approaches underlying these methods are diverse, e.g., trajectory sensitivity [5], extended Kalman filter (EKF) [6], nonlinear least square technique [7], Newton Raphson [8] and Euler [9]. Despite having advantages over offline methods, these techniques have some limitations.…”