Performing security analysis of large scale power systems with a broker-based computational grid

A solution to the online power system security analysis is presented. For complex networks this analysis requires large computational efforts whereas computation times should be less than few minutes for the information to be useful. Even though many architectures based on conventional parallel and distributed systems have been proposed in literature, none of them is able to furnish useful results for large electrical networks. To address this problem, a distributed Web-based architecture integrating a hierarchical grid system is proposed to implement a computational engine able to execute the power system state equations for large electrical networks. The grid system adopts a resource broker to satisfy the quality of service constraints specified by the user. The resulting framework, deployed on a network of heterogeneous clusters and PCs, is used to compute the contingencies analysis of a realistic electrical grid. The experimental results demonstrate that online security analysis can be executed in few minutes even for large network complexity.

[1]  Paul Douglas,et al.  Proceedings International Conference on Information Technology: Coding and Computing , 2002, Proceedings. International Conference on Information Technology: Coding and Computing.

[2]  David Abramson,et al.  An Evaluation of Economy-based Resource Trading and Scheduling on Computational Power Grids for Parameter Sweep Applications , 2000 .

[3]  K. Morison.  Power system security in the new market environment: future directions , 2002, IEEE Power Engineering Society Summer Meeting,.

[4]  A. Monticelli,et al.  Static security analysis using pipeline decomposition , 1998 .

[5]  Rajkumar Buyya,et al.  A taxonomy and survey of grid resource management systems for distributed computing , 2002, Softw. Pract. Exp..

[6]  Eugenio Zimeo,et al.  A Broker Architecture for Object-Oriented Master/Slave Computing in a Hierarchical Grid System , 2003, PARCO.

[7]  E. Zimeo,et al.  A Portable Middleware for Building High-Performance Metacomputers , 2002 .

[8]  Richard Wolski,et al.  The network weather service: a distributed resource performance forecasting service for metacomputing , 1999, Future Gener. Comput. Syst..

[9]  Andrew S. Grimshaw,et al.  Legion: An Operating System for Wide-Area Computing , 1999 .

[10]  Jack J. Dongarra,et al.  The PVM Concurrent Computing System: Evolution, Experiences, and Trends , 1994, Parallel Comput..

[11]  Daniel G. Bobrow,et al.  Book review: The Art of the MetaObject Protocol By Gregor Kiczales, Jim des Rivieres, Daniel G. and Bobrow(MIT Press, 1991) , 1991, SGAR.

[12]  Andrew S. Grimshaw,et al.  Wide-Area Computing: Resource Sharing on a Large Scale , 1999, Computer.

[13]  Franco Frattolillo,et al.  A component-based approach to build a portable and flexible middleware for metacomputing , 2002, Parallel Comput..

[14]  Barry Koren,et al.  Using Coordination to Parallelize Sparse-Grid Methods for 3-D CFD Problems , 1998, Parallel Comput..

[15]  Mario A. Bochicchio,et al.  A distributed computing approach for real-time transient stability analysis , 1997 .

[16]  Peter Sommerlad,et al.  Pattern-Oriented Software Architecture: A System of Patterns: John Wiley & Sons , 1987 .

[17]  Alfredo Vaccaro,et al.  Java-based distributed architectures for intensive computations related to electrical grids , 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..

[18]  Ian T. Foster,et al.  Globus: a Metacomputing Infrastructure Toolkit , 1997, Int. J. High Perform. Comput. Appl..

[19]  Ian T. Foster,et al.  The Anatomy of the Grid: Enabling Scalable Virtual Organizations , 2001, Int. J. High Perform. Comput. Appl..

[20]  Francine Berman,et al.  Master/slave computing on the Grid , 2000, Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556).