Evaluation of Counter-Based Dynamic Load Balancing Schemes for Massive Contingency Analysis on over 10,000 Cores

Contingency analysis studies are necessary to assess the impact of possible power system component failures. The results of the contingency analysis are used to ensure the grid reliability, and in power market operation for the feasibility test of market solutions. Currently, these studies are performed in real time based on the current operating conditions of the grid with a set of pre-selected contingency list, which might result in overlooking some critical contingencies caused by variable system status. To have a complete picture of a power grid, more contingencies need to be studied to improve grid reliability. High-performance computing techniques hold the promise of being able to perform the analysis for more contingency cases within a much shorter time frame. This paper evaluates the performance of counter-based dynamic load balancing schemes for a massive contingency analysis program on 10,000+ cores. One million N-2 contingency analysis cases with a Western Electricity Coordinating Council power grid model have been used to demonstrate the performance. The speedup of 3964 with 4096 cores and 7877 with 10240 cores are obtained. This paper reports the performance of the load balancing scheme with a single counter and two counters, describes disk I/O issues, and discusses other potential techniques for further improving the performance.