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Spatiotemporal Data Mining for Distribution Load ExpansionARANGO, H. G. , LAMBERT-TORRES, G. , de MORAES, C. H. V. , BORGES DA SILVA, L. E.
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data mining, intelligent systems, load modeling, power distribution, urban areas
urban(9), power(9), economic(7), torres(6), systems(6), silva(6), economics(6), data(6), spatial(5), mining(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2016-08-31
Volume 16, Issue 3, Year 2016, On page(s): 65 - 72
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.03010
Web of Science Accession Number: 000384750000010
SCOPUS ID: 84991087193
The load spatial forecasting is fundamental for the electric energy distribution systems planning. Several methods using different conceptions have been proposed to determine the future configuration of the electric markets. This paper proposes a dynamic model of load expansion, based on concepts of local analysis using ideas and applications from urban poles theory. Thus, the load expansion is simulated in a dynamic way, maintaining a continuous change in the conditions for localization of a new load unit. An algorithm generating a snapshot that represents the distribution system configuration at that instant determines the geometry of the market in a given instant. The proposed dynamic model, based on the urban poles theory, has the capacity for summing up the information from economic variables sets, expressed in terms of interchange flow laws, which are modeled by distance and transportation functions. This supplies the model with the capacity for being used even though the number of available explanatory variables is reduced.
|References|||||Cited By «-- Click to see who has cited this paper|
| H. E. Gelani, F. Dastgeer, "Efficiency Analyses of a DC Residential Power Distribution System for the Modern Home," Advances in Electrical and Computer Engineering, vol.15, no.1, pp.135-142, 2015. |
[CrossRef] [Full Text] [Web of Science Times Cited 3] [SCOPUS Times Cited 6]
 A. A. A. Esmin, G. Lambert-Torres, "Application of Particle Swarm Optimization to Optimal Power Systems," International Journal of Innovative Computing, Information and Control, vol.8, no.3A, pp.1705-1716, 2012, Available: http://www.ijicic.org/ijicic-10-12075.pdf
 V.C. do Nacimento, G. Lambert-Torres, C.I.A. Costa, L.E. Borges da Silva, "Control Model for Distributed Generation and Network Automation for Microgrids Operation," Electric Power Systems Research, vol.127, pp.151-159, 2015.
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 7]
 H. G. Arango, A. C. Z. Souza, G. Lambert-Torres, A. P. Alves da Silva, "Difference between Regular and Deterministic Chaos Processes Based on Time Analysis of Load: An Example using CEMIG Data," Electric Power Systems Research, vol.56, no.1, pp.35-41, 2000.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 13]
 H. L. WiIlis, Spatial Electric Load Forecasting, CRC Press, New York, ISBN 9780824708405, 2002.
 Y. Kanemoto, "Evaluating benefits of transportation in models of new economic geography," Economics of Transportation, vol.2, no.2-3, pp.53-63, 2013.
[CrossRef] [SCOPUS Times Cited 3]
 M. Y. Chow, H. Tram, "Application of fuzzy logic technology for spatial load forecasting," IEEE Transactions on Power Systems, vol.12, no.3, pp. 1360-1366, 1997.
[CrossRef] [Web of Science Times Cited 30] [SCOPUS Times Cited 46]
 A. R Ganguly, K. Steinhaeuser, "Data Mining for Climate Change and Impacts," Proc. IEEE Int. Conf. Data Mining Workshop, ICDMW08, IEEE Press, Pisa, pp.385-394, 2008.
[CrossRef] [SCOPUS Times Cited 30]
 R. Trasarti, F. Pinelli, M. Nanni, "Mining Mobility User Profiles for Car Pooling," Proc. 17th ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining, KDD 11, ACM Press, San Diego, CA, pp. 1190-1198, 2011.
[CrossRef] [SCOPUS Times Cited 78]
 H. S. Moghadama, M. Helbich, "Spatiotemporal urbanization processes in the megacity of Mumbai, India: A Markov chains - cellular automata urban growth model," Applied Geography, vol.40, pp.240-249, 2013.
[CrossRef] [Web of Science Times Cited 59] [SCOPUS Times Cited 87]
 M. P. Coutinho, G. Lambert-Torres, L. E. Borges da Silva, H. Lazarek, "A Rough Set Classification Algorithm for Detecting Attacks on Electric Power Systems and Other Critical Structures," The International Journal of Forensic Computer Science, vol.3, no.1, pp.25-32, 2008.
 A. Mohan, A New Spatio-Temporal Data Mining Method and its Application to Reservoir System Operation, Master Thesis, University of Nebraska, 2014.
 M. R. Vieira, V. Frias-Martinez, N. Oliver, E. Fri´as-Marti´nez, "Characterizing Dense Urban Areas from Mobile Phone-Call Data: Discovery and Social Dynamics," Proc. 2010 IEEE 2nd Int. Conf. Social Computing, IEEE SocialCom 2010, IEEE Press, Minneapolis, MN, 241-248, 2010.
[CrossRef] [SCOPUS Times Cited 29]
 R. B. Gonzatti, S. C. Ferreira, C. H. da Silva, L. E. Borges da Silva, R. R. Pereira, G. Lambert-Torres, "Smart Impedance: A New Way to Look at Hybrid Filters," IEEE Transactions on Smart Grid, vol.7, no.2, pp.837-846, 2016.
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 14]
 J. Smith, M. Rylander, L. Rogers, R. Dugan, "It's All in the Plans: Maximizing the Benefits and Minimizing the Impacts of DERs in an Integrated Grid," IEEE Power and Energy Magazine, vol.13, no.2, pp.20-29.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 22]
 M. Fujita, P. Krugman, "When is the economy monocentric?: von Thünen and Chamberlin unified," Regional Science and Urban Economics, vol.25, no.4, pp.505-528, 1995.
[CrossRef] [Web of Science Times Cited 146] [SCOPUS Times Cited 186]
 M. Berliant, M. Fujita, "The Dynamics of Knowledge Diversity and Economic Growth," Southern Economic Journal, vol.77, no.4, pp.856-884, 2011, Available: http://www.jstor.org/stable/23057315.
 Y. Kanemoto, "Second-best cost-benefit analysis in monopolistic competition models of urban agglomeration," Journal of Urban Economics, vol.76, pp.83-92, 2013.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 6]
 M. Fujita, "The Evolution Of Spatial Economics: From Thünen To The New Economic Geography," The Japanese Economic Review, vol.61, no.1, pp.1-32, 2010.
[CrossRef] [Web of Science Times Cited 18] [SCOPUS Times Cited 21]
 G. Duranton, M. A. Turner, "Urban Growth and Transportation," Review of Economic Studies, vol.79, no.4, pp.1407-1440, 2012.
[CrossRef] [Web of Science Times Cited 94] [SCOPUS Times Cited 114]
 E. L. Glaeser, S. P. Kerr, W. R. Kerr, "Entrepreneurship and Urban Growth: An Empirical Assessment with Historical Mines," Review of Economics and Statistics, vol.97, no.2, pp.498-520, 2015.
[CrossRef] [Web of Science Times Cited 34] [SCOPUS Times Cited 42]
 F. Kung, P. Wang, "A spatial network approach to urban configurations," Canadian Journal of Economics, vol.45, no.1, pp314-344, 2012.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]
 H. G. Arango, G. Lambert-Torres, A.P. Alves da Silva, "Load Evolution for Power System Distribution Planning Studies: An Approach Using Spatial Disorder," Proc. IEEE Int. Conf. Systems, Man and Cybernetics, IEEE SMC-1996, IEEE Press, Beijing, pp.1910-1915, 1996.
 M. Berliant, P. Wang, "Dynamic Urban Models: Agglomeration and Growth," Contributions to Economic Analysis, vol.266, pp.531-581, 2004.
 G. Grigoras, G. Cartina, E. C. Bobric, "Strategies for Power/Energy Saving in Distribution Networks," Advances in Electrical and Computer Engineering, vol.10, no.2, pp.61-64, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 6] [SCOPUS Times Cited 8]
 L. Ingber, "Very fast simulated re-annealing," Mathematical and Computer Modelling, vol.12, no.8, pp.967-973, 1989.
[CrossRef] [Web of Science Times Cited 602] [SCOPUS Times Cited 799]
 Google Earth Pro - Available: http:// www.google.com.br/intl/pt-BR/earth/, accessed in March 3rd, 2015, typing Itajuba-MG.
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