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Title: Real Time Simulation of Power Grid Disruptions

Abstract

DOE-OE and DOE-SC workshops (Reference 1-3) identified the key power grid problem that requires insight addressable by the next generation of exascale computing is coupling of real-time data streams (1-2 TB per hour) as the streams are ingested to dynamic models. These models would then identify predicted disruptions in time (2-4 seconds) to trigger the smart grid s self healing functions. This project attempted to establish the feasibility of this approach and defined the scientific issues, and demonstrated example solutions to important smart grid simulation problems. These objectives were accomplished by 1) using the existing frequency recorders on the national grid to establish a representative and scalable real-time data stream; 2) invoking ORNL signature identification algorithms; 3) modeling dynamically a representative region of the Eastern interconnect using an institutional cluster, measuring the scalability and computational benchmarks for a national capability; and 4) constructing a prototype simulation for the system s concept of smart grid deployment. The delivered ORNL enduring capability included: 1) data processing and simulation metrics to design a national capability justifying exascale applications; 2) Software and intellectual property built around the example solutions; 3) demonstrated dynamic models to design few second self-healing.

Authors:
 [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1082004
Report Number(s):
ORNL/TM-2012/483
DOE Contract Number:  
DE-AC05-00OR22725
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English

Citation Formats

Chinthavali, Supriya, Dimitrovski, Aleksandar D, Fernandez, Steven J, Groer, Christopher S, Nutaro, James J, Olama, Mohammed M, Omitaomu, Olufemi A, Shankar, Mallikarjun, Spafford, Kyle L, and Vacaliuc, Bogdan. Real Time Simulation of Power Grid Disruptions. United States: N. p., 2012. Web. doi:10.2172/1082004.
Chinthavali, Supriya, Dimitrovski, Aleksandar D, Fernandez, Steven J, Groer, Christopher S, Nutaro, James J, Olama, Mohammed M, Omitaomu, Olufemi A, Shankar, Mallikarjun, Spafford, Kyle L, & Vacaliuc, Bogdan. Real Time Simulation of Power Grid Disruptions. United States. doi:10.2172/1082004.
Chinthavali, Supriya, Dimitrovski, Aleksandar D, Fernandez, Steven J, Groer, Christopher S, Nutaro, James J, Olama, Mohammed M, Omitaomu, Olufemi A, Shankar, Mallikarjun, Spafford, Kyle L, and Vacaliuc, Bogdan. Thu . "Real Time Simulation of Power Grid Disruptions". United States. doi:10.2172/1082004. https://www.osti.gov/servlets/purl/1082004.
@article{osti_1082004,
title = {Real Time Simulation of Power Grid Disruptions},
author = {Chinthavali, Supriya and Dimitrovski, Aleksandar D and Fernandez, Steven J and Groer, Christopher S and Nutaro, James J and Olama, Mohammed M and Omitaomu, Olufemi A and Shankar, Mallikarjun and Spafford, Kyle L and Vacaliuc, Bogdan},
abstractNote = {DOE-OE and DOE-SC workshops (Reference 1-3) identified the key power grid problem that requires insight addressable by the next generation of exascale computing is coupling of real-time data streams (1-2 TB per hour) as the streams are ingested to dynamic models. These models would then identify predicted disruptions in time (2-4 seconds) to trigger the smart grid s self healing functions. This project attempted to establish the feasibility of this approach and defined the scientific issues, and demonstrated example solutions to important smart grid simulation problems. These objectives were accomplished by 1) using the existing frequency recorders on the national grid to establish a representative and scalable real-time data stream; 2) invoking ORNL signature identification algorithms; 3) modeling dynamically a representative region of the Eastern interconnect using an institutional cluster, measuring the scalability and computational benchmarks for a national capability; and 4) constructing a prototype simulation for the system s concept of smart grid deployment. The delivered ORNL enduring capability included: 1) data processing and simulation metrics to design a national capability justifying exascale applications; 2) Software and intellectual property built around the example solutions; 3) demonstrated dynamic models to design few second self-healing.},
doi = {10.2172/1082004},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2012},
month = {11}
}

Technical Report:

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