High Performance Computing in Power and Energy System
[Book]
/ edited by Siddhartha Kumar Khaitan, Anshul Gupta
Berlin, Heidelberg
: Springer Berlin Heidelberg :Imprint: Springer,
, 2013.
XIV, 379 p. 164 illus., online resource.
(Power Systems,1612-1287)
Electronic
The twin challenge of meeting global energy demands in the face of growing economies and populations and restricting greenhouse gas emissions is one of the most daunting ones that humanity has ever faced. Smart electrical generation and distribution infrastructure will play a crucial role in meeting these challenges. We would need to develop capabilities to handle large volumes of data generated by the power system components like PMUs, DFRs and other data acquisition devices as well as by the capacity to process these data at high resolution via multi-scale and multi-period simulations, cascading and security analysis, interaction between hybrid systems (electric, transport, gas, oil, coal, etc.) and so on, to get meaningful information in real time to ensure a secure, reliable and stable power system grid. Advanced research on development and implementation of market-ready leading-edge high-speed enabling technologies and algorithms for solving real-time, dynamic, resource-critical problems will be required for dynamic security analysis targeted towards successful implementation of Smart Grid initiatives. This books aims to bring together some of the latest research developments as well as thoughts on the future research directions of the high performance computing applications in electric power systems planning, operations, security, markets, and grid integration of alternate sources of energy, etc.
From the contents: High Performance Computing in Electrical Energy Systems Applications -- High Performance Computing for Power System Dynamic Simulation -- Distributed Parallel Power System Simulation -- A MAS-Based Cluster Computing Platform for Modern EMS -- High-Performance Computing for Real-Time Grid Analysis and Operation -- Dynamic Load Balancing and Scheduling for Parallel Power System Dynamic Contingency Analysis.