Análisis de Consumo de Energía Eléctrica Usando Análisis de Componentes Independientes
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ISSN: 1680-8894
E-ISSN: 2219-6714
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Enviado:
Jun 28, 2016
Publicado: Jun 28, 2016
Publicado: Jun 28, 2016
Resumen
Este documento presenta un método para el análisis de la serie de tiempo de consumo eléctrico utilizando Análisis de Componentes Independientes (ICA). Con este método es posible detectar y extraer de manera automática factores que influyen separadamente en el consumo eléctrico, así como estudiar su relación en la curva de consumo diario con ayuda de perfiles estimados paralelamente con ICA. ICA logra aislar estos comportamientos en un grupo de componentes sin perder representatividad de los datos ofreciendo una visión más profunda del consumo eléctrico con el objetivo de facilitar su modelado y pronóstico.
Palabras clave
Análisis de componentes independientes, análisis de series de tiempo, consumo de energía eléctrica.Descargas
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Cómo citar
Boya, C. (2016). Análisis de Consumo de Energía Eléctrica Usando Análisis de Componentes Independientes. I+D Tecnológico, 10(2), 48-55. Recuperado a partir de https://revistas.utp.ac.pa/index.php/id-tecnologico/article/view/24
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Modelling Practice and Theory, Vol. 25, pp. 190–205, Jun. 2012.
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short- term load forecasting: a review and evaluation”, I E E E
Transaction on Power Systems, Vol. 16, no. 1, pp. 44-55, Feb. 2001.
(3) S.M Al-Alawi, S.M. Islam, “Principles of electricity demand
forecasting Part1. Methodologies”, Power Engineering Journal,
Vol. 10, no. 3, pp. 139-143, Jun. 1996.
(4) B. L. Bowerman, R. T. O’Connell, A. B. Koehler, Pronósticos,
Series de Tiempo y Regresión, Un Enfoque Aplicado, Cengage
Learning Editores , 2009.
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Springer-Verlag, New York, USA, 2002.
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Chatzarakis, S.K. Katsikas, P. Liatsis, "Electricity demand loads
modeling using AutoRegressive Moving Average (ARMA)
models", Energy, Vol. 33, no. 9, pp. 1353-1360, Sept. 2008.
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Weighted methods ", IEEE transactions on Power Systems, Vol.
27, no. 1, pp. 458-640, Feb. 2012.
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component analysis to extracting structure from stock returns”,
International journal of neural systems, Vol. 8, no. 4, pp. 473-484,
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parallel 2nancial time series”, In Proc. Int. Conf. on Neural
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with independent component analysis”, In Proc. Int. Conf. on
Advanced Investment Technology, Gold Coast, Autralia, October,
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series”, Adaptive Systems for Signal Processing,
Communications, and Control Symposium 2000, Alberta, Canada,
4 Oct. 2000.
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Signal processing, Vol. 36, no. 3, pp. 287-314, April 1994.
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Background Activity With Independent Component Analysis",
IEEE Transactions on Biomedical Engineering, Vol. 54, no. 11, pp.
1965-1973, 2007.
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from simultaneously recorded EEG and fMRI data using
independent component analysis", IEEE Transactions on
Biomedical Engineering, Vol. 53, no. 7, pp. 1294-1308, 2006.
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acoustic speaker tracking and time–frequency masking”,
Computer Speech &Language, Vol. 27, pp. 683-702, May 2013.
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multiple-output wireless communication systems", Signal
Processing, Vol. 91, no. 4, pp. 607-623, April 2011.
(17) T. Ju, et al., "Blind Source Separation of Mixed PD Signals
Produced by Multiple Insulation Defects in GIS," IEEE
Transactions on Power Delivery, Vol. 25, no. 3, pp. 170-176, Jan.
2010.
(18) C.H. Chen, “The use of independent component analysis
as a tool for data mining”, Geoscience and remote sensing
symposium, Toronto, Canada, 24-28 June, 2002.
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independent component analysis and support vector
regression”, Decision Support Systems, Vol. 47, no. 2, pp. 115-
125, May 2009.
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Independent Component Analysis”, IEEE Transactions on
Neural Networks, Vol. 10, no. 3, pp. 626-634, May 1999.
(21) ICA y BSS group, “The FastICA software package”, [online]:
“http://research.ics.aalto.fi/ica/fastica/. Ultimo acceso:
23 de mayo de 2014.
(22) A. Hyvarinen, et. al., Independent component analysis:
algorithms and applications, Wiley, New York, USA, 2001.
(23) M.A.A. Lima, A.S. Cerqueira, D.V. Coury, C.A. Duque, “A novel
method for power quality multiple disturbance decomposition
based on Independent Component Analysis”, International
Journal of Electrical Power & Energy Systems, Vol. 42, no. 1, pp.
593-604, Nov. 2012.
(24) B. Mijovic, M.D. Vos, I. Gligorijevic, J. Taelman, S.V. Huffel,
“Source Separation From Single-Channel Recordings by
Combining Empirical-Mode Decomposition and Independent
Component Analysis”, IEEE transactions on biomedical
engineering, Vol. 57, no. 9, pp. 2188-2196, Sept. 2010.
(25) ETESA, “Comportamiento del sistema”, Centro de Nacional
de despacho [online], Disponible: http://www.cnd.com.pa/
informes.php?cat=5, Accesado: 2 de Junio de 2014.