Feasibility of satisfying projected biopower demands in support of decarbonization interventions: A spatially-explicit cost optimization model applied to woody biomass in the eastern US

Ashkan Mirzaee, Ronald G. McGarvey and Francisco Aguilar

Energy Economics, 2024, vol. 136, issue C

Abstract: Power generation from biomass (biopower) has experienced substantial growth in the United States. Although renewable and sustainably sourced biopower can reduce the carbon footprint of the electricity sector, there is a scarcity of analyses that simultaneously consider the financial feasibility and sustainability criteria of procured biomass. We developed a spatially-explicit optimization model to minimize the cost of meeting projected biopower demand while ensuring carbon neutrality and biomass sustainability constraints. The optimization model was applied to projected biopower demand scenarios in the eastern US, considering various public policy decarbonization interventions. Modeling woody biomass procured from local forests as the source of biopower was chosen due to its dominant role as a renewable energy source, regional availability, and lower risk of violating carbon neutrality objectives. Initially, we projected the net growth of woody biomass in trees and their carbon pools by 2035, as a function of biopower generation, utilizing data from 2009–2017. Subsequently, forecasted woody biomass and projected biopower demand through 2035 were employed to determine optimal levels of biopower generation and estimate the corresponding resource impacts within procurement forests. The results suggest the potential for substantial increases in sustainable biopower generation in the eastern US. However, the feasibility of this expansion depends on the continued economic viability of biopower generation in the future. It is worth noting that the largest increases, surpassing threefold, in biopower generation over the 2020–2030 decade could potentially compromise the carbon neutrality of locally procured woody biomass.

Keywords: Biopower; Spatial-explicit optimization; Forest; Biomass (search for similar items in EconPapers)
JEL-codes: C33 C44 Q23 Q42 Q56 R19 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:136:y:2024:i:c:s0140988324003803

DOI: 10.1016/j.eneco.2024.107672

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