Pervasive grid for large-scale power systems contingency analysis

Optimal control and management of power systems require extensive analyses of phenomena that can compromise their operation in order to evaluate their impact on the security and reliability levels of the electrical networks. For complex networks, this process, known as power systems contingencies analysis, requires large computational efforts, whereas computation times should be less than a few minutes for the information to be useful. Even though many architectures based on conventional parallel and distributed systems have been widely proposed in the literature, they are characterized by low extensibility, reusability, and scalability, and so, they require a sensible hardware upgrade when more computational resources are necessary. This event is not infrequent in power systems where the constant growth of the electrical network complexity and the need for larger security and reliability levels of the plant infrastructures lead to the need of more detailed contingency analysis in shorter times. To address this problem, this paper proposes a pervasive grid approach to define a user-friendly software infrastructure for data acquisition from electrical networks and for data processing in order to simulate possible contingencies in a real electrical network. The grid infrastructure adopts a brokering service, based on an economy-driven model, to satisfy the quality of service constraints specified by the user (i.e., a time deadline to simulate the contingencies). This paper also discusses the deployment of the infrastructure on a network of heterogeneous clusters and PCs to compute the contingency analysis of a realistic electrical network. The experimental results obtained demonstrate the effectiveness of the proposed solution and the potential role of grid computing in supporting intensive computations in power systems

[1]  Enrico Gobbetti,et al.  Encyclopedia of Electrical and Electronics Engineering , 1999 .

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

[3]  Domenico Villacci,et al.  Performing security analysis of large scale power systems with a broker-based computational grid , 2004, International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004..

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

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

[6]  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.

[7]  C. W. Taylor.  The future in on-line security assessment and wide-area stability control , 2000, 2000 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.00CH37077).

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

[9]  Ronald H. Perrott,et al.  Grid Based Virtual Bioinformatics Laboratory , 2003 .

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

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

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

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

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

[15]  Daniel Tylavsky,et al.  Parallel processing in power systems computation , 1992 .

[16]  Francine Berman,et al.  High-performance schedulers , 1998 .

[17]  Osvaldo R. Saavedra,et al.  Solving the security constrained optimal power flow problem in a distributed computing environment , 1996 .

[18]  Alfredo Vaccaro,et al.  A distributed architecture for online power systems security analysis , 2004, IEEE Transactions on Industrial Electronics.

[19]  David Abramson,et al.  Economic models for resource management and scheduling in Grid computing , 2002, Concurr. Comput. Pract. Exp..

[20]  G. Taylor,et al.  Plug in to grid computing , 2004, IEEE Power and Energy Magazine.

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

[22]  Eugenio Zimeo,et al.  An economy-driven mapping heuristic for hierarchical master-slave applications in grid systems , 2006, Proceedings 20th IEEE International Parallel & Distributed Processing Symposium.

[23]  Gordon S. Blair,et al.  A Middleware Approach for Pervasive Grid Environments , 2005 .

[24]  Kevin Tomsovic,et al.  Power System Security , 1999 .

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

[26]  J.C.O. Mello,et al.  Dynamic security risk assessment , 1999, 1999 IEEE Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.99CH36364).