SN Applied Sciences (May 2021)

Design of profitable networks of biogas plants in Chile

  • R. Casas,
  • F. Casas,
  • J. Bustos

DOI
https://doi.org/10.1007/s42452-021-04605-5
Journal volume & issue
Vol. 3, no. 6
pp. 1 – 23

Abstract

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Abstract Locations for profitable biogas plant networks for the generation of electric power were investigated. A population-based location algorithm was developed. Using information regarding biogas power and plants cost found in the literature, together with data on the location and number of dairy cows of 572 farms in southern Chile, economic analises were made. Each farm was evaluated as a potencial location for a biogas plant, both alone and as part of different combinations. The algorithm starts with a population of one-plant combinations and generates new iterations by inserting additional biogas plants as long as the NPV increases. In each iteration, only a diverse subset of the combinations is selected. This approach is compared to the application of the ArcGIS Network Analyst (NA) function for the set cover problem, usually employed in the literature for biogas plant network location problems. Using the technical parameters for the operation of biogas plants found in the literature, we show that the proposed algorithm gives better results than the NA algorithm in terms of profit. Biogas plant networks were obtained for different scenarios of biomass availability (40–80%), energy sale prices (90–100 USD/MWh) and transport costs (0.3–0.4 USD/tkm). The results indicate that 18 of the 572 farms would be good candidates to site a biogas plant in at least one of the scenarios. A maximum of eight farms appear in a scenario with 80% of biomass availability and a transport cost of 0.3 USD/tkm. This solution reaches a NPV of USD 3,538,394, which exceeds by more than 70% the USD 2,075,057 obtained with the solution retrieved by the NA function. As the algorithm presented obtained better results than the ArcGIS network analyst, it can be used as an appropriate design tool for biogas plant networks.

Keywords