4.8 Article

Stochastic modelling of the economic viability of on-farm co-digestion of pig manure and food waste in Ireland

期刊

APPLIED ENERGY
卷 205, 期 -, 页码 1528-1537

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2017.08.101

关键词

Biogas; Monte Carlo simulation; Finance; Substrate availability; Renewable electricity tariff

资金

  1. Green Farm project - Science Foundation Ireland Investigator Project Award [12/IP/1519]
  2. Science Foundation Ireland (SFI) [12/IP/1519] Funding Source: Science Foundation Ireland (SFI)

向作者/读者索取更多资源

The majority of studies analysing the economic potential of biogas systems utilise deterministic models to assess the viability of a system using fixed inputs. However, changes in market conditions can significantly affect the viability of biogas plants, and need to be accounted for. This study assessed the economic potential of undertaking on-farm anaerobic co-digestion of food waste (FW) and pig manure (PM) using both deterministic and stochastic modelling approaches. The financial viability of three co-digestion plants sized to treat PM generated from 521, 2607 and 5214 sow integrated units was assessed. Under current market conditions the largest co-digestion scenario modelled was found to be unviable. Stochastic modelling of four key input variables (FW availability, renewable electricity tariff, gate fees and digestate disposal costs) was undertaken to assess the sensitivity of project viability to changes in market conditions. Due to the high likelihood of accessing sufficient FW, the smallest co-digestion scenario was found to be the least sensitive to any future changes in market conditions. Due to its potential to treat greater amounts of FW than the smallest scenario, a co-digestion plant designed for a 2607 sow farm had the highest revenue generating potential under optimal market conditions; however, it was more sensitive to changes in FW availability than the smaller scenario. This study illustrates the need for farm-based biogas plant projects to secure long-term, stable supplies of co-substrates and to size plants' capacity based on the availability of the co-substrates which drive methane production (and revenue generation).

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