Final report for %22High performance computing for advanced national electric power grid modeling and integration of solar generation resources%22, LDRD Project No. 149016.

Reno, Matthew J. ; Riehm, Andrew Charles ; Hoekstra, Robert John ; Munoz-Ramirez, Karina ; Stamp, Jason Edwin ; Phillips, Laurence R. ; Adams, Brian M. ; Russo, Thomas V. ; Oldfield, Ron A. ; McLendon, William Clarence, III ; Nelson, Jeffrey Scott ; Hansen, Clifford W. ; Richardson, Bryan T. ; Stein, Joshua S. ; Schoenwald, David Alan ; Wolfenbarger, Paul R.

Sandia National Laboratories

关键词: 24 Power Transmission And Distribution;    Simulation;    Control Systems;    Design;    Transients;   

DOI  :  10.2172/1011206
RP-ID  :  SAND2011-0890
RP-ID  :  AC04-94AL85000
RP-ID  :  1011206

美国|英语

来源: UNT Digital Library

【 摘 要 】

Design and operation of the electric power grid (EPG) relies heavily on computational models. High-fidelity, full-order models are used to study transient phenomena on only a small part of the network. Reduced-order dynamic and power flow models are used when analysis involving thousands of nodes are required due to the computational demands when simulating large numbers of nodes. The level of complexity of the future EPG will dramatically increase due to large-scale deployment of variable renewable generation, active load and distributed generation resources, adaptive protection and control systems, and price-responsive demand. High-fidelity modeling of this future grid will require significant advances in coupled, multi-scale tools and their use on high performance computing (HPC) platforms. This LDRD report demonstrates SNL's capability to apply HPC resources to these 3 tasks: (1) High-fidelity, large-scale modeling of power system dynamics; (2) Statistical assessment of grid security via Monte-Carlo simulations of cyber attacks; and (3) Development of models to predict variability of solar resources at locations where little or no ground-based measurements are available.