2017/01/18 by Mushfiqur R. Sarker, Jianhui Wang, Sarker, Mushfiqur R. +1
Computer Science · Engineering · #Distributed #Electric Power System Optimization #FOS: Computer and information sciences #Optimal Power Flow Distribution #Parallel #Smart Grid Energy Management #and Cluster Computing (cs.DC) #cs.DC
paper · pdf · doi:10.48550/arxiv.1702.03886
2 pages, 1 figure, 1 table, IEEE Letter
arxiv created 2017/01/18 · openalex publication_date 2017/01/18 · arxiv updated 2017/02/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The advent of High Performance Computing (HPC) has provided the computational capacity required for power system operators (SO) to obtain solutions in the least time to highly-complex applications, i.e., Unit Commitment (UC). The UC problem, which attempts to schedule the least-cost combination of generating units to meet the load, is increasing in complexity and problem size due to deployments of renewable resources and smart grid technologies. The current approach to solving the UC problem consists of in-house HPC infrastructures, which experience issues at scale, and demands high maintenance and capital expenditures. On the other hand, cloud computing is an ideal substitute due to its powerful computational capacity, rapid scalability, and high cost-effectiveness. In this work, the benefits and challenges of outsourcing the UC application to the cloud are explored. A quantitative analysis of the computational performance gain is explored for a large-scale UC problem solved on the cloud and compared to traditional in-house HPC infrastructure. The results show substantial reduction in solve time when outsourced to the cloud.