Dynamic Load Balancing and Scheduling for Parallel Power System Dynamic Contingency Analysis

Abstract

Power system simulations involving solution of thousands of stiff differential and algebraic equations (DAE) are extremely computationally intensive and yet crucial for grid security and reliability. Online simulation of minutes to hours for a large number of contingencies requires computational efficiency several orders of magnitude greater than what is todays state-of-the-art. We have developed an optimized simulator for single contingency analysis using efficient numerical algorithms implementation for solving DAE, and scaled it up for large-scale contingency analysis using MPI. A prototype parallel high speed extended term simulator (HSET) on in-house high performance computing (HPC) resources at Iowa State University (ISU) (namely Cystorm Supercomputer) is being developed. Since the simulation times across contingencies vary considerably, we have focused our efforts towards development of efficient scheduling algorithms through work stealing for maximal resource utilization and minimum overhead to perform faster than real time analysis. This chapter introduces a novel implementation of dynamic load balancing algorithm for dynamic contingency analysis. Results indicate potential for significant improvements over the state-of-the-art methods especially master-slave based load balancing typically used in power system community. Simulations of thousands of contingencies on a large real system were conducted and computational savings and scalability results are reported.