Massachussets Institute of Technology. Cambridge (United States of America)
July 30th, 1981
Summary:
This thesis concerns the understanding and simplification of complicated models of dynamic systems or processes (such as those that challenge the engineer, the economist, the system theorist or the scientist). A fundamentally new approach for addressing these issues, Selective Modal Analysis (or SMA), is presented.
SMA is a framework for accurate, efficient and physically-based modeling and analysis of selected portions of the structure and behavior of linear time-invariant (or LTI) systems. With SMA, the part of the model that is relevant to the dynamics of interest is singled out in a direct manner, and the remainder of the model is collapsed in a way that leaves the selected structure and behavior intact. The integrating viewpoint of SMA ties together, in a conceptually simple but rigorous fashion, issues in eigenanalysis, determination and decoupling of dynamic patterns, model interpretation and reduction, input-output characterization of models, modal control, and so on.
SMA encompasses a variety of concepts that can find application in the study of LTI models of any size. However, when applied to largescale systems, the techniques and algorithms provided by SMA have the potential of significantly reducing the computational costs and the numerical ill-conditioning problems that are commonplace in the analysis of such systems. SMA is particularly well suited to the study of composite models, i.e., models formulated as a collection of dynamica subsystems that are interconnected by static constraints.
Although SMA is not restricted to any particular kind of system, only one specific application, namely the so-called Dynamic Stability problem in electric power systems, has been considered in some depth. SMA has the potential to be made the basis fora a comprehensive (and so far nonexistent) approach to this problem. SMA-based algorithms can accept the hign-dimensional models needed for Dynamic Stability analysis, can accurately and efficiently analyze these models to assess the stability conditions of the system, and can feed the resultant information to an appropiate control scheme. Preliminary guidelines are also provided for application of the SEMA concepts to other power system problems, such as coherency identification or construction of modal dynamic equivalents.
Citation:
I.J. Pérez-Arriaga (1981), Selective modal analysis with applications to electric power systems. Massachussets Institute of Technology. Cambridge (United States of America).
