International Journal of
Physical Sciences

  • Abbreviation: Int. J. Phys. Sci.
  • Language: English
  • ISSN: 1992-1950
  • DOI: 10.5897/IJPS
  • Start Year: 2006
  • Published Articles: 2533

Full Length Research Paper

Control response of electric demand by means of fuzzy logic using programmable logic controller (PLC)

J. L. Rojas-Rentería1,3*, G. Macias-Bobadilla1, R. Luna-Rubio1,3, C. A. Gonzalez-Gutierrez1, A. Rojas-Molina1 and J. L. González-Pérez2
1División de Estudios de Posgrado, Facultad de Ingeniería, Universidad Autónoma de Querétaro. Cerro de las Campanas S/N, C. P. 76010, Querétaro, Qro., México. 2Aplicaciones Computacionales y Biotecnología, Facultad de Ingeniería, Universidad Autónoma de Querétaro. Cerro de las Campanas S/N, C.P. 76010, Querétaro, Qro., México. 3Universidad Tecnológica de Corregidora, Carretera a Coroneo km 11.5, Querétaro, Qro. México.
Email: [email protected]

  •  Accepted: 24 April 2013
  •  Published: 30 May 2013

Abstract

This paper presents a controller of the electricity energy consumption for intelligent buildings. Special reference is made to a fuzzy control structure implemented in a programmable logic controller (PLC). Here the function of PLC is not only to connect and disconnect loads in the building, but to make use of vague terms from fuzzy reasoning. Using the class schedule, estimated consumption demand and the actual value, temperature and electric rates were used as a variables input to the controller for taking control action on the percentage of activation of ballasts for lighting lamps inside the building. A monitoring system was performed to forecast energy consumption in the building by means of artificial neural networks (ANN) as support for fuzzy control. The electricity consumption control has become an issue at the monthly bill that keeps record of that electricity consumption. The goal is to have a control that allows us a better management of the energy system and therefore savings on the final consumer, having a more uniform distribution of electricity consumption for building loads.

 

Key words: Fuzzy control, artificial neural networks, energy, programmable logic control.