Modelo para la Predicción Energética de una Instalación Hotelera

  1. Adriana V. Acosta 1
  2. Jesús M. Zamarreño 2
  3. Ana I. González 1
  4. Víctor Álvarez 3
  1. 1 Instituto Superior Politécnico José Antonio Echeverría
  2. 2 Universidad de Valladolid
    info

    Universidad de Valladolid

    Valladolid, España

    ROR https://ror.org/01fvbaw18

  3. 3 Hotel Meliá Habana
Mostrar afiliaciones +
Revista:
Revista iberoamericana de automática e informática industrial ( RIAI )

ISSN: 1697-7920

Año de publicación: 2011

Volumen: 8

Número: 4

Páginas: 309-322

Tipo: Artículo

DOI: 10.1016/J.RIAI.2011.09.001 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Revista iberoamericana de automática e informática industrial ( RIAI )

Resumen

Este artículo describe la obtención y validación de un modelo de predicción energética para el hotel Meliá Habana de la ciudad Habana en Cuba. El modelo obtenido emplea el método de series de tiempo radiantes para la determinación de la carga térmica de los bloques habitacionales de la instalación. El modelo es implementado en el lenguaje de programación MatLab®. La validación experimental del modelo se realiza con mediciones reales del consumo energético diario del hotel. El valor de uso del modelo obtenido es apreciable para estudios de comportamiento energético y para la implementación de estrategias avanzadas de control.

Referencias bibliográficas

  • Acosta C. A, and A.I. González, 2007. Primera aproximación a un modelo de predicciones energéticas de habitación hotelera. Simposio CIE 2007. Santa Clara, Cuba.
  • Acosta C.A., A. I. González and V. Castelló, 2008a Obtención de un modelo de predicciones energéticas de habitación hotelera. Conferencia FIE2008. Santiago de Cuba, Cuba.
  • Acosta C. A., A. I. González, J.M. Zamarreño and V. Castelló, 2008b. A model for energy predictions of a hotel room. 20th European Modeling and Simulation Symposium. (Simulation in Industry). Briatico, Italy
  • ASHRAE,1997. ASHRAE Handbook. Chapter 28, Nonresidential cooling and heating load calculation procedures. ASHRAE Handbook Editor.
  • ASHRAE, 2005a. ASHRAE Handbook. Chapter 30, Nonresidential cooling and heating load calculation procedures. ASHRAE Handbook Editor.
  • ASHRAE, 2005b ASHRAE Handbook. Chapter 32, Energy Estimating and modeling methods. ASHRAE Handbook Editor.
  • ASHRAE. 2007. ASHRAE Handbook. Chapter 5, Hotels, Motels, and Dormitories. ASHRAE Handbook Editor.
  • ASHRAE. 2009. ASHRAE Handbook. Chapter 15, Fenestration. ASHRAE Handbook Editor.
  • Budaiwi I.M,.2003. Air conditioning system operation strategies for intermittent occupancy building in a hot -sumid climate. King Fahd University of petroleum and minerals architectural, Engineering Department. Proceedings: Building Simulation 2007.
  • Castilla, M.M., J. D. Alvarez, M. Berenguel, M. Pérez, F. Rodríguez and J.L. Guzmán. 2010. Técnicas de control del confort en edificios. RIAI Vol. 7, No. 3, pp 5-24.
  • Crawley D.B., L.K. Lawrie, F.C. Winkelmann, W.F. Buhl, Y. Joe Huang, C.O. Pedersen, R.K. Strand, R.J. Liesen, D.E. Fisher, M.J. Witte, and J. Glazer., 2001. EnergyPlus: Creating a new-generation building energy simulation program. Energy and Buildings 33(4):319-331.
  • D. Li, T. Lam, W. Chan and A. Mak, 2009. Energy and cost analysis of semi-transparent photovoltaic in office buildings. Applied Energy, 19 pp 722–729.
  • F. Gugliermetti, G. Passerini and F. Bisegna, 2004. Climate models for the assessment of office buildings energy performance. Building and Environment, Vol. 39, pp 39-50.
  • Fangting Song, Yi Jiang, Anne Le Mouel and Jean-Jacques Roux, 2007. Development of a data model for energy consumption analysis and prediction of large-scale commercial buildings. Proceedings: Building Simulation 2007, pp 1601.
  • Fumio Sakurai, Dr. Tatsuo Inooka, Dr. Ryuji Yanagihara , Etsuo Higashizawa, Junya Hamane, Tatsuo Fujii, Hisashi Nishihata, Hideto Hayashi, Fumihiro ArizumiHiroshi Ninomiya, Kazusa Koik Naoko Shinohara, 2007. FACES (Forecast of air-conditioning system’s energy, environmental, and economical, performance by simulation). Proceedings: Building Simulation 2007. Japan.
  • González Santos A. I., 1996. Sistema de regulación automático para controlar el índice de confort en ambientes climatizados. Tesis de Maestría en Automática, ISPJAE. Cuba.
  • Hernández N. A., Sanzovo Fiorelli F. A., 2007 Use of simulation tools managing buildings energy demand. Proceedings: Building Simula Conference 2007, pp 1883.
  • Hittle, D.C., 1999. The effect of beam solar radiation on peak cooling loads. ASHRAE Transactions, 105(2):510-13.
  • Ip Seng Iu., 2002. Experimental validation of the radiant time series method for cooling load calculations. Thesis of the Degree of Mast of Science. Oklahoma State University
  • Iu, Pisen Calvin, 2004. PRF/RTF Generator Software.
  • Ljung and Lennart, 1999. System Identification theory for the user. Prentice Hall 2nd edition.
  • M. A. Aktacir, O. Büyükalaca, H. Bulut and T. Yilmaz,.2008. Influence of different outdoor design conditions on design cooling load and design capacities of air conditioning equipments. Energy Conversion and Management, 49, 6, pp. 1766-1773.
  • MathWorks, 2007. Matlab 7.4.0. Ayuda de la herramienta, versión 7.0.
  • McQuiston, F.C. and J.D. Spitler, 1992. Cooling and heating load calculation manual. 2nd ed. ASHRAE.
  • Mingxian Cui and Tingyao Chen., 2009. A revised radiant time series (RTS) method for intermittent cooling load calculation. Eleventh International IBPSA Conference. Glasgow, Scotland.
  • Pantelis N. Botsaris and Spyridon Prebezanos., 2004. A methodology for a thermal energy building audit. Building and Environment, Vol.39, pp. 195 – 199.
  • Pedrini, F.S. Westphal and R. Lamberts, 2002. A methodology for building enegy modeling and calibration in warm climates. Buildings and Environment, Vol. 37, pp 903 – 912.
  • S. Chirarattananon and J. Taveekun,.2004. An OTTV-based energy estimation model for commercial buildings in Thailand. Energy and Buildings, Vol. 36, Issue 7, July, pp 680-689.
  • Sowell E.F. ,1988. Cross-check and modification of the DOE-2 program for calculation of zone weighting factors. ASHRAE Transactions 94 (2):737-53.
  • Spitler J.D. and D.E. Fisher. 1999. Development of periodic response factors for use with the raciant time series method. ASHRAE Transactions, 105(2)
  • T. Chen and M. Cui, 2010. A RTS-based method for direct and consistent calculating intermittent peak cooling loads. Energy Conversion and Management, 51, 6, pp. 1170-1178.
  • Trott A. R. and Welch T, 2000. Refrigeration and air-conditioning., Third edition by Butterworth-Heinemann.
  • U.S. Army,1979. BLAST, the building loads analysis and system thermodynamics programa - Users manual. U.S. Army Construction Engineering Research Laboratory Report E-153.l
  • US Department of Energy, 2005. ENERGYPLUSTM, Input Output Reference.
  • Westphal F.S. and R. Lamberts., 2005. Building Simulation Calibration Using Sensitivity Analysis. 9th International IBPSA Conference, August.
  • Y. Pan, Z. Huang, G. Wu and C. Chen.,2006. The application of building energy simulation and calibration in two high rise commercial buildings in Shangai. Proceedings: Building Simulation Conference 2007, pp 1889.
  • Yik F.W.H., J. Burnett and I. Prescott, 2001. Predicting air-conditioning energy consumption of a group of buildings using different heat rejection methods. Energy and Buildings, Vol. 33, pp 151-166.
  • York D.A. and C.C. Cappiello, eds, 1982. DOE-2 engineers manual. Lawrence Berkeley Laboratory Report LBL-11353 (LA-8520-M, DE83004575). National Technical Information Services, Springfield, VA.
Fuente de los datos: Dialnet