Stochastic techno-economic analysis of electricity produced from poplar plantations in Indiana

RENEWABLE ENERGY

卷:149

Article

Jeong, Dawoon¹  Tyner, Wallace E.¹  Meilan, Richard²  Brown, Tristan R.³  Doering, Otto C.¹ 

[1] Purdue Univ, Dept Agr Econ, 403 West State St, W Lafayette, IN 47907 USA

[2] Purdue Univ, Dept Forestry & Nat Resources, Purdue Ctr Plant Biol, W Lafayette, IN 47907 USA

[3] SUNY Coll Environm Sci & Forestry, Dept Forest & Nat Resources Management, Syracuse, NY 13210 USA

关键词: Stochastic techno-economic analysis;    Life-cycle assessment (LCA);    Short-rotation coppice (SRC) poplar;    Biopower;    Renewable electricity;   

DOI  :  10.1016/j.renene.2019.11.061

来源: Elsevier

【 摘 要 】

This study evaluates the economic and global-warming potential for a 100% biomass direct-fire biopower plant in Indiana using short-rotation coppice poplar (Populus spp.) as a feedstock. The poplar yield and moisture content data were collected from an actual field trial conducted in southern Indiana beginning in 2013. Monte-Carlo simulation was applied to account for uncertainty in three parameters (poplar yield, moisture content, and planting costs). We found that the biopower plant is economically infeasible in Indiana, as the estimated system breakeven price (21.5 cents/kWh) is six times higher than the current wholesale electricity price in Indiana. Based on the LCA analysis, we found that this pathway has negative net emissions (-1.14 kg CO2 eq/ kWh), due to carbon sequestration. As a coal-intensive power-generating state, Indiana would require a carbon tax above $93.5/ton CO2-equivalent to make the biopower plant competitive with other types of power plants (coal and natural gas). This analysis was based on average-quality land. We then conducted a sensitivity analysis using poor- and high-quality land. There are small, statistically significant differences between land types, but likely they are not economically significant because the data we have for the three land rents are subject to high uncertainty, which could not be quantified. (C) 2019 Elsevier Ltd. All rights reserved.

【 授权许可】

Free