A Distributed-computing-based Eigenvalue Algorithm for Stability Analysis of Large-scale Power Systems

This paper describes a distributed-computing-based eigenvalue algorithm for the small signal stability analysis of large-scale power transmission networks. Modern large-scale interconnected power systems often consist of a number of independently controlled and operated transmission networks, where the detailed network structure, status and data of each independent transmission area is not usually available to other areas, so in this case the conventional centralized-computing-based methods may be impractical. The algorithm proposed in this paper introduces a two-layer distributed iteration method to compute eigenvalues of the state matrix, which only needs the involved areas use their local network structure, status, data and a few of intermediate variables exchanged from the boundary area. The algorithm has been successfully tested on the IEEE 9-bus system.