© The Institution of Engineering and Technology
With the deregulation and constant expansion in power systems, the demand of high performance computing (HPC) for power system adequacy and security analysis has been increased rapidly. HPC also plays an important role in ensuring efficient and reliable communication for power system operation and control. In past few years, grid computing technology is catching up much attention from the power engineers and researchers. Grid computing technology is an infrastructure, which can provide HPC and communication mechanism for providing services in these areas of power system. A review is presented on the research which has been carried out in the last few years in this area regarding the applicability of grid computing technology in power system reliability and security analysis, operations, monitoring and control systems. We also introduce more grid computing applications for the future research directions in order to provide more open access and more efficient and effective computing services to meet the increasing needs of the power industry. This review presents a comprehensive and clear picture of the benefits of using this technology in terms of efficiency and cost.
References
-
-
1)
-
Chen, Y., Shen, C., Zhang, W., Song, Y.: `II-GRID: grid computing infrastructure for power systems', 39thInternational Universities Power Engineering Conf. 2004 (UPEC 2004), September 2004, p. 1204–1208.
-
2)
-
I. Foster ,
C. Kesselman ,
J.M. Nick ,
S. Tuecke
.
The physiology of the grid: an open grid services architecture for distributed systems integration.
-
3)
-
Ali, M., Dong, Z.Y., Li, Z., Zhang, P.: `A grid computing based approach for probabilistic load flow analysis', APSCOM 2006, October/November 2006, Hong Kong.
-
4)
-
Zeng, L., Lei, H.: `A semantic publish/subscribe system', IEEE Int. Conf. E-Commerce Technology for Dynamic E-Business (CEC-East'04), September 2004, p. 32–39.
-
5)
-
M. Shahidehpour ,
Y. Wang
.
(2003)
Communication and control in electric power systems; applications of parallel and distributed processing.
-
6)
-
LEGION, Worldwide Virtual Computer, University of Virginia, VA, available at: http://legion.virginia.edu.
-
7)
-
J.C. Das
.
(2002)
Power system analysis: short-circuit load flow and harmonics.
-
8)
-
Wang, H., Liu, Y.: `Power system restoration collaborative grid based on grid computing environment', IEEE Power Engineering Society General Meeting 2005, June 2005, San Francisco.
-
9)
-
Asadzadeh, P., Buyya, R., Kei, C.L., Nayar, D., Venugopal, S.: `Global grids and software toolkits: a study of four grid middleware technologies', Technical Report GRIDS-TR-2004–4, July 2004, Australia.
-
10)
-
Wu, F.F., Moslehi, K., Bose, A.: `Power system control centers: past, present, and future', Proc. IEEE, November 2005, 93, p. 1890–1908.
-
11)
-
GridCC Plug into Computers Nationwide for Alternative Energy, Brunel University, London, UK, January 2005, available at: http://www.brunel.ac.uk/news/pressoffice/pressreleases/2005/cdata/january/gridcc0105/.
-
12)
-
GridPP: UK Computing for Particle Physics, available at: http://www.gridpp.ac.uk, accessed June 2005.
-
13)
-
L. Ferreira ,
V. Berstis
.
(2002)
Fundamentals of grid computing, IBM Redbooks.
-
14)
-
Taylor, G.A., Irving, M.R., Axon, C., Hobson, P.R.: `Scalable integration of wind power on transmission systems using grid computing', Sixth International Workshop on Large-scale Integration of Wind Power & Transmission Networks for Offshore Wind Farms, October 2006, Delft, The Netherlands, p. 181–187.
-
15)
-
Globus Alliance, available at: http://www.globus.org/.
-
16)
-
EUROGRID Project: Application Testbed for European GRID Computing, available at: http://www.eurogrid.org/.
-
17)
-
I. Foster
.
(2002)
The grid: a new infrastructure for 21st century science, Physics Today.
-
18)
-
NASA Information Power Grid (IPG) Infrastructure, available at: http://www.gloriad.org/gloriad/projects/project000053.html.
-
19)
-
Sheng, S., Li, K.K., Xiangjun, Z.: `Grid computing for load modeling', IEEE Int. Conf. Electric Utility Deregulation, Restructuring and Power Technologies 2004, April 2004, p. 602–605.
-
20)
-
I. Foster ,
C. Kesselman ,
S. Tuecke
.
The anatomy of the grid: enabling scalable virtual organizations.
Int. J. Supercomput. Appl.
,
3 ,
200 -
222
-
21)
-
Zhau, H.F., Wu, F.F.: `Data service in grid-based future control centers', Seventh IEE International Conf. Advances in Power System Control, Operation and Management (APSCOM 2006), 2006, Hong Kong.
-
22)
-
Taylor, G.A., Irving, M.R., Hobson, P.R., Huang, C., Kyberd, P., Taylor, R.J.: `Distributed monitoring and control of future power systems via grid computing', IEEE PES General Meeting 2006, June 2006, Montreal, Canada.
-
23)
-
Axceleon and Power Technologies Inc. (PTI) Partner to Deliver Grid Computing Solution for Top Global Electricity Transmission Company (Axceleon Inc., USA), available at: http://www.axceleon.com/press/release030318.html, accessed March 2003.
-
24)
-
TeraGrid: National Science Foundation, available at: http://www.teragrid.org.
-
25)
-
Ali, M., Dong, Z.Y., Li, X., Zhang, P.: `RSA-grid: a grid computing based framework for power system reliability and security analysis', IEEE-PES General Meeting 2006, June 2006, Montreal, Canada.
-
26)
-
Al-Khannak, R., Bitzer, B.: `Load balancing for distributed and integrated power systems using grid computing', Int. Conf. Clean Electrical Power 2007 (ICCEP'07), May 2007.
-
27)
-
Global Ring Network for Advanced Applications Development, available at: http://www.gloriad.org/gloriad/index.html.
-
28)
-
Grid Enabled Remote Instrumentation with Distributed Control and Computation, available at: http://www.gridcc.org/, accessed July 2007.
-
29)
-
Li, Z., Liu, Y.: `Reactive power optimization using agent-based grid computing', The Seventh Int. Power Engineering Conf. 2005 (IPEC 2005), November/December 2005.
-
30)
-
Zhang, P., Stephen, , Lee, T., Sobajic, D.: `Moving toward probabilistic reliability assessment methods', Eighth Int. Conf. Probabilistic Methods Applied to Power Systems, September 2004, USA, Iowa State University.
-
31)
-
Xu, Z., Ali, M., Dong, Z.Y., Li, X.: `A novel grid computing approach for probabilistic small signal analysis', IEEE PES 2006 General Meeting, June 2006, Montreal, Canada.
-
32)
-
Particle Physics Data Grid Collaboratory Pilot (PPDG), available at: http://www.ppdg.net/.
-
33)
-
BIRN (Biomedical Informatics Research Network), available at: http://www.nbirn.net/index.shtm.
-
34)
-
Huang, Q., Qin, K., Wang, W.: `A software architecture based on multi-agent and grid computing for electric power system applications', Int. Symp. Parallel Computing in Electrical Engineering 2006 (PAR ELEC 2006), 2006, p. 405–410.
-
35)
-
Ali, M., Dong, Z.Y., Li, X., Zhang, P.: `Applications of grid computing in power systems', Australian Universities Power Engineering Conf. AUPEC 2005, September 2005, Hobart, Australia.
-
36)
-
‘Axceleon and Power Technologies Inc. deliver grid computing for global electricity transmission company’. Primeur Monthly, available at: http://www.hoise.com/primeur/03/articles/monthly/AE-PR-04-03-104.html.
-
37)
-
A. Grimshaw ,
H. Kishimoto ,
A. Savva
.
The open grid services architecture, Version 1.0.
-
38)
-
Grid Physics Network: National Science Foundation, available at: http://www.griphyn.org/.
-
39)
-
Mohsin, A., Dong, Z.Y., Zhang, P., Xue, L.: `Probabilistic transient stability analysis using grid computing technology', IEEE Power Engineering Society General Meeting 2007, June 2007, Tampa, FL, USA, p. 1–7.
-
40)
-
Huang, C., Hobson, P.R., Taylor, G.A., Kyberd, P.: `A study of publish/subscribe systems for real-time grid monitoring', Parallel and Distributed Processing Symp. 2007 (IPDPS 2007) IEEE Int., March 2007, Long Beach, CA, USA.
-
41)
-
Sakamoto, N., Ozawa, K., Niimura, T.: `Grid computing solutions for artificial neural network-based electricity market forecasts', 2006 Int. Joint Conf. Neural Networks, July 2006, Vancouver, BC, Canada, p. 4382–4386.
-
42)
-
M. Irving ,
G. Taylor ,
P. Hobson
.
Plug in to grid computing, moving beyond the web, a look at the potential benefits of grid computing for future power networks.
IEEE Power Energy Mag.
,
40 -
44
-
43)
-
R. Billinton ,
W. Li
.
(1994)
Reliability assessment of electric power systems using Monte Carlo methods.
-
44)
-
Zhou, H.F., Wu, F.F., Ni, Y.X.: `Design for grid service-based future power system control centers', APSCOM 2006, October/November 2006, Hong Kong.
-
45)
-
Condor, High Throughput Computing, The University of Wisconsin, Madison, available at: http://www.cs.wisc.edu/condor/.
-
46)
-
Ali, M., Dong, Z.Y., Li, X., Zhang, P.: `Applications of grid computing in power systems', Australasian Universities Power Engineering Conf. (AUPEC 2005), September 2005, Hobart, Australia.
-
47)
-
Jing, C., Zhang, P.: `Online dynamic security assessment based on grid computing architecture', APSCOM 2006, October/November 2006, Hong Kong.
-
48)
-
M. Cannataro ,
D. Talia
.
The knowledge grid.
Commun. ACM
,
1 ,
89 -
93
-
49)
-
UNICORE (Uniform Interface to Computing Resources): ‘Distributed computing and data resources’. Distributed Systems and Grid Computing, Juelich Supercomputing Centre, Research Centre Juelich, available at: http://www.unicore.eu.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2009.0076
Related content
content/journals/10.1049/iet-gtd.2009.0076
pub_keyword,iet_inspecKeyword,pub_concept
6
6