An Electrical Energy Consumption Monitoring and Forecasting System

  • J. L. Rojas-Renteria Engineering Dpt, Autonomous Universityof Queretaro, Mexico
  • T. D. Espinoza-Huerta Faculty of Accounting and Administration, Autonomous University of Queretaro, Mexico
  • F. S. Tovar-Pacheco Industrial Maintenance and Construction Dpt, Technological University of San Juan del Rio, Mexico
  • J. L. Gonzalez-Perez Linking Dpt, Polytechnic University of Santa Rosa Jauregui, Mexico
  • R. Lozano-Dorantes Engineering Dpt, Anahuac University, Mexico
Keywords: power consumption, energy monitoring, heuristic methods


Electricity consumption is currently an issue of great interest for power companies that need an as much as accurate profile for controlling the installed systems but also for designing future expansions and alterations. Detailed monitoring has proved to be valuable for both power companies and consumers. Further, as smart grid technology is bound to result to increasingly flexible rates, an accurate forecast is bound to prove valuable in the future. In this paper, a monitoring and forecasting system is investigated. The monitoring system was installed in an actual building and the recordings were used to design and evaluate the forecasting system, based on an artificial neural network. Results show that the system can provide detailed monitoring and also an accurate forecast for a building’s consumption.


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P. Soderholm, “The political economy of international green certificate markets”, Energy Policy,Vol. 36, No. 6, pp. 2051– 2062, 2008

N. Truong, L. Wanga, P. K. C. Wong “Modelling and short-term forecasting of daily peak power demand in Victoria using two-dimensional wavelet based SDP models”, Electrical Power and Energy Systems, Vol. 30, pp. 511-518, 2008

J. K. W. Wong, H. Li, S. W. Wang, “Intelligent building research: a review”, Automation in Construction, Vol. 14, pp. 143–159, 2009

G. Wood, M. Newborough, “Energy-use information transfer for intelligent homes: Enabling energy conservation with central and local displays”, Energy and Buildings, Vol. 39, No. 4, pp. 495-503, 2006

J. E. Seem, “Using intelligent data analysis to detect abnormal energy consumption in buildings”, Energy and Buildings, Vol. 39, No. 1, pp. 52-58, 2006

J. L. Rojas-Renteria, G. Macias-Bobadilla, R. Luna-Rubio, C. A. Gonzalez-Gutierrez, A. Rojas-Molina, J. L. Gonzalez-Perez “Control response of electric demand by means of fuzzy logic using programmable logic controller (PLC)”, International Journal of Physical Sciences, Vol. 8, No. 20, pp. 1058-1067, 2013

Y. S. Kim, K. S. Kim, “Simplified energy prediction method accounting for part-load performance of chiller”, Building and Environment, Vol. 42, No. 1, pp. 507-515, 2007

J J. L. Rojas-Renteria. R. Luna-Rubio, J. L. Gonzalez-Perez, C. A. Gonzalez-Gutierrez, A. Rojas-Molina, G. Macias-Bobadilla, “Estimated electric power consumption by means of artificial neural networks and autoregressive models with exogenous input methods”, International Journal of Physical Sciences, Vol. 8, No. 14, pp. 585-592, 2013

H. Doukas, K. D. Patlitzianas, K. Iatropoulos, J. Psarras, “Intelligent building energy management system using rule sets”, Building and Environment, Vol. 42, No. 10, pp. 3562-3569, 2007

J. K. Pal, F. C. Huff, “Advantages of an electrical control and energy management system”, ISA Transactions, Vol. 39, No. 1, pp. 103-114, 2000


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