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Title: Dynamic Contingency Analysis Tool

The Dynamic Contingency Analysis Tool (DCAT) is an open-platform and publicly available methodology to help develop applications that aim to improve the capabilities of power system planning engineers to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. Outputs from the DCAT will help find mitigation solutions to reduce the risk of cascading outages in technically sound and effective ways. The current prototype DCAT implementation has been developed as a Python code that accesses the simulation functions of the Siemens PSS�E planning tool (PSS/E). It has the following features: It uses a hybrid dynamic and steady-state approach to simulating the cascading outage sequences that includes fast dynamic and slower steady-state events. It integrates dynamic models with protection scheme models for generation, transmission, and load. It models special protection systems (SPSs)/remedial action schemes (RASs) and automatic and manual corrective actions. Overall, the DCAT attempts to bridge multiple gaps in cascading-outage analysis in a single, unique prototype tool capable of automatically simulating and analyzing cascading sequences in real systems using multiprocessor computers.While the DCAT has been implemented using PSS/E in Phase I of the study, other commercial software packages with similar capabilities can bemore » used within the DCAT framework.« less
Publication Date:
OSTI Identifier:
1311621
Report Number(s):
DCAT; 004613MLTPL00
30834-E
DOE Contract Number:
AC05-76RL01830
Software Revision:
00
Software Package Number:
004613
Software CPU:
MLTPL
Open Source:
Yes
Contact PNNL Technology Commercialization; http://availabletechnologies.pnnl.gov/
Source Code Available:
Yes
Other Software Info:
Open Source. May be available through PNNL Software Portal and is available on an individual basis through PNNL Technology Commercialization office.
Related Software:
The current prototype DCAT implementation has been developed as a Python code that accesses the simulation functions of the Siemens PSS´┐ŻE planning tool (PSS/E)
Research Org:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Org:
USDOE Office of Electricity Delivery and Energy Reliability (OE)
Contributing Orgs:
Battelle Memorial Institute, Pacific Northwest Division (PNNL)
Country of Publication:
United States

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