Abstract
A GIS-based methodology to identify the optimal locations for biomass extraction plants and biomass power plants is presented. Both agricultural land suitability criteria and logistic criteria were taken into account to select the optimal locations. Agricultural land suitability criteria were included as several independent variables of edaphic and climate conditions. A generalized additive model (GAM) was developed for estimating crop yield by using those edaphic and climate independent variables in potential zones where crops of interest are not currently grown, planted or seeded. Logistic criteria were incorporated in the model via network analysis of the available roads for the accessibility of each zone. Using a saturation approach of candidate locations, it was possible to generate a ranked list of sites for the project development. This list can be sent as input to an energy supply chain optimization model
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
A Location—Allocation analysis requires two sets of input data: “Facilities” and “Demand Points”. In this ArcGIS tool, “Facilities” are defined as generic production plants and “Demand points” are the customers for its products. For this case the interpretation is taken backwards: “Demand points” will produce biomass and “Facilities” will demand that biomass.
- 2.
In Fig. 13 values are multiplied by 10.
- 3.
In Fig. 16, values are multiplied by 10.
- 4.
These values were amplified by a factor 10, in order to avoid errors in the software ArcGIS® which has troubles handling very low values.
References
Fischer G, Schrattenholzer L (2001) Global bioenergy potentials through 2050. Biomass Bioenergy 20:151–159
Freppaz D, Minciardi R, Robba M, Rovatti M, Sacile R, Taramasso A (2004) Optimizing forest biomass exploitation for energy supply at a regional level. Biomass Bioenergy 26:15–25
Panichelli L, Gnansounou E (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 Bioenergy 32:289–300
Searcy E, Flynn P, Ghafoori E, Kumar A (2007) The relative cost of biomass energy transport. Appl Biochem Biotechnol 137–140:639–652
Silverman B (1986) Density estimation for statistics and data analysis. Chapman and Hall, New York
Sultana A, Kumar A (2012) Optimal siting and size of bioenergy facilities using geographic information system. Appl Energy 94:192–201
UPME, et.al (2010) Atlas del Potencial Energético de la Biomasa Residual en Colombia. UPME, Bogotá
Voivontas D, Assimacopoulos D, Koukios EG (2001) Assessment of biomass potential for power production: a GIS based method. Biomass Bioenergy 20:101–112
Wullschleger SD, Davis EB, Borsuk ME, Gunderson CA, Lynd LR (2010) Biomass Production in Switchgrass across the United States: database description and determinants of yield. Agron J. 102:1158–1168
Yu H, Wang Q, Ileleji KE, Yu C, Luo Z, Cen K et al (2012) Design and analysis of geographic distribution of biomass power plant and satellite storages in China. Part 1: straight-line delivery. Biomass Bioenergy 46:773–784
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Morales-Rincón, L., Martínez, A., Avila-Díaz, F.B., Acero, J.R., Castillo-Monroy, E.F., Uribe-Rodríguez, A. (2015). Gis-Based Methodology for Optimum Location of Biomass Extraction Plants and Power Plants Using Both Logistic Criteria and Agricultural Suitability Criteria. In: Eksioglu, S., Rebennack, S., Pardalos, P. (eds) Handbook of Bioenergy. Energy Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-20092-7_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-20092-7_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-20091-0
Online ISBN: 978-3-319-20092-7
eBook Packages: EnergyEnergy (R0)