Mathematical Model and Software for Multiple Location of Co-Generation Energy Plants: A Case Study in Southern Regions of Chile

Mathematical Model and Software for Multiple Location of Co-Generation Energy Plants: A Case Study in Southern Regions of Chile

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Author(s)

Author(s): Juan A. Gomez, Juan Pablo Concha, Bruno Neumann

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705 1252 93-104 Volume 2 - Mar 2013

Abstract

This paper addresses the issue of locating and determining the area of supply of various cogeneration energy plants, based on forest biomass. Two models are proposed, binary and mixed programming, depending on whether or not to allow the intersection between supply areas. Each model computes the ideal places to install biomass plants and their respective supply areas of raw material, since the latter are handled implicitly by the decision variables. We also propose two solution strategies depending on the size of the problem: Branch and cut algorithm for problems of medium size and heuristics associated with a genetic algorithm for large problems. We also develop software that automates the construction of the appropriate model, based on information provided by the user, delivering the optimal locations together with supply areas for the number and type of plants desired.

Keywords

Cogeneration energy, Biomass forestry, Multiple Location, Mixed and Binary Programming, Genetic Algorithm

References

  1. Bernetti, I., C. Fagarazzi, R. Fratini., 2004. A methodology to analyze the potential development of biomass energy sector: an application in Tuscany, Forest Policy and Economics. 415-432
  2. Esteban, L.S., P. Pérez Ortiz, P. Ciria, J. Carrasco., 2000. Evaluación de los recursos de biomasa forestal en la provincia de Soria. Análisis de alternativas para su aprovechamiento energético. Colección Documentos CIEMAT, Centro de Investigaciones Energéticas Medioambientales y Teconológicas. 124
  3. Goldberg, D., 1989. Genetic algorithm in search, optimization and machine learning. Addison Wesley
  4. Graham, R.L., B.C. English, C.E. Noon.,2000. A Geographic Information System-based modelling system for evaluating the cost of delivered energy crop feedstock. Biomass and Bioenergy, 309-329
  5. Guerrero F., A. Carrazo., 2005. Localización de centrales de energìa eléctrica a partir de biomasa procedente de olivar. Revista de Estudios Regionales. 153-175
  6. GUROBI, Mathemathical Programming Software, http://www.gurobi.com
  7. Krukanont, P., S. Prasertsan., 2004. Geographical distribution of biomass and potential sites of rubber wood fired power plants in Southern Thailand. Biomass and Bioenergy. 47-59
  8. Mitchell, M., 1996. An introduction to genetic algorithms. MIT Edit
  9. Panichelli, L., E. Gnansounou., 2008. GIS-based approach for defining bioenergy facilities location: A case study in Northern Spain based on marginal delivery costs and resources competition between facilities. Biomass and Bioenergy. 289-300
  10. Pontt, C. Estudio de contribución de las ERNC al SIC al 2025 (Potencial de Biomasa en Chile), Technical Report, Universidad Técnica Federico Santa Marìa, 2008
  11. Rentizelas A.A., I.P. Tatsiopoulos, A. Tolis., 2009. An optimization model for multi-biomass tri-generation energy supply. Biomass and Bioenergy. 223-233
  12. Troncoso J., R. Garrido., 2002. Modelos de localización de instalaciones: una aplicación para la producción y logìstica forestal. Scielo. 57-67
  13. Voivontas, D., D. Assimacopoulos, E.G. Koukios., 2001. Assessment of biomass potential for power production: a GIS based method. Biomass and Bioenergy. 101-112
  14. Wolsey, L. A.,1998 , Integer Programming, Wiley-Interscience publication
  15. Xun Shi, A. Elmore., 2008. Using spatial information technologies to select sites for biomass power plants: A case study in Guangdong Province, China. Biomass and Bioenergy. 35-43

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International Journal of Sciences is Open Access Journal.
This article is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License.
Author(s) retain the copyrights of this article, though, publication rights are with Alkhaer Publications.

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