Accelerating the Computation of Critical Eigenvalues with Parallel Computing Techniques


Eigenanalysis of power systems is frequently used to study the effect and tune the response of existing controllers, or to guide the design of new controllers. However, recent developments in the area lead to the necessity of studying larger power system models, resulting from the interconnection of transmission networks or the joint consideration of transmission and distribution networks. Moreover, these models include new types of controls, mainly based on power electronic interfaces, which are expected to provide significant support in the future. The consequence is that the size and complexity of these models challenge the computational efficiency of existing eigenanalysis methods. In this paper, a procedure is proposed that uses domain decomposition and parallel computing methods, to accelerate the computation of eigenvalues in a selected region of the complex plane with iterative eigenanalysis methods. The proposed algorithm is validated on a small transmission system and its performance is assessed on a large-scale, combined transmission and distribution system.

Proc. of 2016 PSCC Conference