Simplified Power System Models for Dynamic Stability Studies

An on-Line Optimal Artificial Neural Network-Based Controller for Simplified Order Power Systems

“…The complete data of this system are given in appendix (b). The model reduction technique is given in [2], which is used for reducing the 13 th order model of generating unit (A,B in Eqn.1) to 5 th order model (A, ,B r in Eqn.5). At nominal operating point P=.75, Q=0.0 and the reduced order models is calculated as follows: Table 1 gives the eigenvalues of both the original and reduced order models and the corresponding time response is dedicated in Fig.…”

“…Therefore, the analysis of dynamic stability and controller's design of these large interconnected power systems becomes time consuming and laborious in order to have an accordance order representation of high-order power systems, model reduction techniques are used for getting simplified models with adequate accordance. Several methods for model reduction are based on eigenvalue analysis of the system linearized differential equations [1,2]. Davison [1] had used the eigenvalues and eigenvectors of the complete system model to compute a reduced model of smaller order than the original.…”

2 Model order reduction in mechanical engineering

“…Modal methods can be applied either to second-order models (common in multibody systems [48,24,1,33,84]) or to state-space representations. Corresponding methods were intensively developed from the 1960s onwards ( [25,73,23,20] and Chapter 4 of Volume 1 of Model order reduction) and are applied in other areas of engineering as well, for instance in the reduction of power systems [64] and for the purpose of control design, e. g., [71,66,58,7]. With the advent of balanced truncation and of Krylov subspace methods ( [78,44], [42,45], overviews in [4,8,10], and Chapters 2 and 3 of Volume 1 of Model order reduction) the approximation quality and the applicability to high-and very high-order linear systems improved significantly and opened numerous fields of applications.…”

Model reduction of power systems based on the balanced residualization method

“…C OMPLICATED power systems generally consist of hundreds of generators and thousands of buses, which consumes abundant time and computer memory during power system dynamic analysis and simulation tests [1]. In fact, when studying the power systems, we are just interested in the specific area called study area (SA), whose model should be described in detail.…”