Stability analysis and stabilization of delayed reduced-order model of large electric power system

Abstract

SUMMARYThis paper discusses stability analysis using spectral discretization of time-delayed electric power system. The stability assessment is discussed in terms of influence of time delays on inter-area oscillation modes of the power system models: well-known 4-generator and 14-generator Southeast Australian power system. The three dominant inter-area modes available in full-order power system are retained in its equivalent representation, i.e., reduced-order model, obtained with the input-output variables of the generator that participates actively to low-frequency oscillation modes. The pseudospectrum analysis suggests the most dominant modes to be sensitive against time delay. The rightmost characteristic roots and the robust spectral abscissa are computed over a wide range of time delays in the input-output variables. The approach applied in study computes all the characteristic roots in the right half s-plane with the number of discretization points selected in such a way that rational approximation of the exponential functions remains accurate in this region. The effect of time delays on the computation of spectral abscissa is also investigated. Further, reduced-order time-delayed model is also used to design the wide-area controller by optimizing (minimizing) the robust spectral abscissa.

Development of optimal reduced‐order model for gas turbine power plants using particle swarm optimization technique

“…In a grid connected system, small disturbances can cause sustained oscillation that may lead to system outage . Therefore, it is necessary to analyze the performance of HDGT using model order reduction methods that uses stability criterion .…”

“…In a grid connected system, small disturbances can cause sustained oscillation that may lead to system outage. 15,17 Therefore, it is necessary to analyze the performance of HDGT using model order reduction methods that uses stability criterion. 27 As the stability of the reduced-order model is influenced by the numerator of the original system, 36,37 the mixed approach has been preferred for model order reduction.…”

“…Panda et al revealed that the design, analysis, and controller synthesis for any higher‐order system in real‐time environment are tedious and expensive . In order to overcome this complexity and reduce the computational burden, it is very much essential to identify an equivalent reduced‐order model, which would retain the dominant characteristics of the original system . It is understood from the literature review that only few attempts were made to identify the reduced‐order model of the real‐time system, viz, wind turbine blade system and micro‐turbine system .…”

“…16 In order to overcome this complexity and reduce the computational burden, it is very much essential to identify an equivalent reduced-order model, which would retain the dominant characteristics of the original system. 17 It is understood from the literature review that only few attempts were made to identify the reduced-order model of the real-time system, viz, wind turbine blade system and micro-turbine system. 18,19 Though the previous researchers used the Rowen (1983) model only for dynamic analysis and controller development for HDGT 3,8,10,12 -, 15,20 there were no attempts made to identify the reduced-order model of the HDGT plant.…”

An enhanced and auto-tuned power system stabilizer based on optimized interval type-2 fuzzy PID scheme

“…[7][8][9] Changes in operating condition do not significantly affect the performance of the FPSS. 10 A FPSS can adjust its parameters online according to the conditions and can provide a good damping over a wide range of operating conditions. [11][12][13] In Shokouhandeh et al, 11 an optimized type-1 fuzzy PID controller is used as a PSS for the single machine connected to an infinite bus (SMIB) system.…”