Contingency Analysis Post-Processing With Advanced Computing and Visualization

Journal Article · Sat Jul 01 04:00:00 EDT 2017 · IFAC-PapersOnLine

DOI:https://doi.org/10.1016/j.ifacol.2017.08.010· OSTI ID:1406676

Chen, Yousu; Glaesemann, Kurt; Fitzhenry, Erin

Contingency analysis is a critical function widely used in energy management systems to assess the impact of power system component failures. Its outputs are important for power system operation for improved situational awareness, power system planning studies, and power market operations. With the increased complexity of power system modeling and simulation caused by increased energy production and demand, the penetration of renewable energy and fast deployment of smart grid devices, and the trend of operating grids closer to their capacity for better efficiency, more and more contingencies must be executed and analyzed quickly in order to ensure grid reliability and accuracy for the power market. Currently, many researchers have proposed different techniques to accelerate the computational speed of contingency analysis, but not much work has been published on how to post-process the large amount of contingency outputs quickly. This paper proposes a parallel post-processing function that can analyze contingency analysis outputs faster and display them in a web-based visualization tool to help power engineers improve their work efficiency by fast information digestion. Case studies using an ESCA-60 bus system and a WECC planning system are presented to demonstrate the functionality of the parallel post-processing technique and the web-based visualization tool.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1406676
• Report Number(s): PNNL-SA-122202; TE1103000
• Journal Information: IFAC-PapersOnLine, Journal Name: IFAC-PapersOnLine Journal Issue: 1 Vol. 50; ISSN 2405-8963
• Publisher: Elsevier
• Country of Publication: United States
• Language: English