1st International Workshop on High Performance Computing, Networking and Analytics for the Power Grid
1st International Workshop on High Performance Computing,
Networking and Analytics for the Power Grid
Seattle, WA, USA, November 13, 2011
Sensor deployments on the grid are expected to increase geometrically in the immediate future, while the demand for clean energy generation is driving the use of non-dispatchable power sources, such as solar and wind. New demands are being placed on the power infrastructure due to the introduction of plug-in vehicles. These trends reinforce the need for higher fidelity simulation of power grids, and higher frequency measurement of their state.
Traditional grid simulation and monitoring tools cannot handle the increased amounts of sensor data or computation imposed by these trends. The use of high performance computing and networking technologies is of paramount importance for the future power grid, particularly for its stable operation in the presence of intermittent generation and increased demands placed on its infrastructure.
The workshop intends to promote the use of high performance computing and networking for power grid applications. Technological and policy changes make this an urgent priority.
Daniel Chavarría, chair. Pacific Northwest National Lab, firstname.lastname@example.org
Daniel Kirschen, University of Washington.
Boming Zhang, Tsinghua University.
Terry Oliver, Bonneville Power Administration.
Bora Akyol, chair. Pacific Northwest National Lab.
Henry Huang, chair. Pacific Northwest National Lab.
Jeff Dagle Pacific Northwest National Lab.
Mihai Anitescu, Argonne National Laboratory.
David Bakken, Washington State University.
Patrick Panciatici, Réseau de transport d'électricité.
Gilbert Bindewald, US Department of Energy.
This workshop is sponsored in part by the Future Power Grid Initiative (FPGI), a laboratory directed research & development initiative at the Pacific Northwest National Lab (PNNL). The goal of the FPGI is to develop the next-generation algorithms and tools for networking, modeling and simulation, and visualization and decision support to drive the transformation towards a more reliable and efficient future power grid. The FPGI technical approach is to combine PNNL's distinctive capabilities in power systems, data intensive computing, high performance computing, and visual analytics to address the complex problems from these real-time and large-scale challenges.
Daniel G. Chavarría
Pacific Northwest National Laboratory
902 Battelle Boulevard
P.O. Box 999, MSIN: J4-30
Richland, WA 99352 USA