Empirical Insights into Economic Viability: Integrating Bitcoin Mining with Biorefineries Using a Stochastic Model Article Swipe
Georgeio Semaan
,
Guizhou Wang
,
Tunç Durmaz
,
Gopalakrishnan Kumar
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/systems13050359
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/systems13050359
This study explores integrating Bitcoin mining with lignocellulosic biorefineries to create an additional revenue stream. Profits from mining can help offset internal costs, reduce business expenses, or lower consumer prices. Using sensitivity analysis and Monte Carlo simulations, this study identifies key profitability drivers, such as electricity costs, hardware expenses, starting year, and operational time. Time emerged as an extremely sensitive factor and showed that delaying mining operations significantly raised production costs and the probability of profitable outcomes. In contrast, longer mining durations had a smaller yet sizable impact. Hardware costs, computational efficiency, and electricity prices also strongly influenced the outcomes. The majority of simulated events showed a loss. Moreover, the model showed that the marginal profitability of mining decreases over time. Nonetheless, the model demonstrated that under favourable conditions, it is possible to integrate Bitcoin mining into biorefineries and other productive ventures, thereby allowing for cost recovery using Bitcoin profits. For a biorefinery to mine Bitcoin and maximise cost recovery, it must start early, access low electricity prices, and preserve hardware capital characterised by low expenditure and high revenues. Finally, a discussion about the opportunities, risks, and regulations is highlighted.
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- en
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All OpenAlex metadata
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Empirical Insights into Economic Viability: Integrating Bitcoin Mining with Biorefineries Using a Stochastic ModelWork title
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enPrimary language
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2025Year of publication
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2025-05-07Full publication date if available
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Georgeio Semaan, Guizhou Wang, Tunç Durmaz, Gopalakrishnan KumarList of authors in order
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https://doi.org/10.3390/systems13050359Publisher landing page
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https://www.mdpi.com/2079-8954/13/5/359/pdf?version=1746623313Direct link to full text PDF
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2079-8954/13/5/359/pdf?version=1746623313Direct OA link when available
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| abstract_inverted_index.Profits | 15 |
| abstract_inverted_index.capital | 171 |
| abstract_inverted_index.emerged | 55 |
| abstract_inverted_index.impact. | 87 |
| abstract_inverted_index.prices, | 167 |
| abstract_inverted_index.prices. | 29 |
| abstract_inverted_index.revenue | 13 |
| abstract_inverted_index.sizable | 86 |
| abstract_inverted_index.smaller | 84 |
| abstract_inverted_index.stream. | 14 |
| abstract_inverted_index.thereby | 142 |
| abstract_inverted_index.Finally, | 179 |
| abstract_inverted_index.Hardware | 88 |
| abstract_inverted_index.allowing | 143 |
| abstract_inverted_index.analysis | 32 |
| abstract_inverted_index.business | 24 |
| abstract_inverted_index.consumer | 28 |
| abstract_inverted_index.delaying | 64 |
| abstract_inverted_index.drivers, | 42 |
| abstract_inverted_index.explores | 2 |
| abstract_inverted_index.hardware | 47, 170 |
| abstract_inverted_index.internal | 21 |
| abstract_inverted_index.majority | 101 |
| abstract_inverted_index.marginal | 114 |
| abstract_inverted_index.maximise | 157 |
| abstract_inverted_index.possible | 131 |
| abstract_inverted_index.preserve | 169 |
| abstract_inverted_index.profits. | 149 |
| abstract_inverted_index.recovery | 146 |
| abstract_inverted_index.starting | 49 |
| abstract_inverted_index.strongly | 96 |
| abstract_inverted_index.Moreover, | 108 |
| abstract_inverted_index.contrast, | 78 |
| abstract_inverted_index.decreases | 118 |
| abstract_inverted_index.durations | 81 |
| abstract_inverted_index.expenses, | 25, 48 |
| abstract_inverted_index.extremely | 58 |
| abstract_inverted_index.integrate | 133 |
| abstract_inverted_index.outcomes. | 76, 99 |
| abstract_inverted_index.recovery, | 159 |
| abstract_inverted_index.revenues. | 178 |
| abstract_inverted_index.sensitive | 59 |
| abstract_inverted_index.simulated | 103 |
| abstract_inverted_index.ventures, | 141 |
| abstract_inverted_index.additional | 12 |
| abstract_inverted_index.discussion | 181 |
| abstract_inverted_index.favourable | 127 |
| abstract_inverted_index.identifies | 39 |
| abstract_inverted_index.influenced | 97 |
| abstract_inverted_index.operations | 66 |
| abstract_inverted_index.production | 69 |
| abstract_inverted_index.productive | 140 |
| abstract_inverted_index.profitable | 75 |
| abstract_inverted_index.biorefinery | 152 |
| abstract_inverted_index.conditions, | 128 |
| abstract_inverted_index.efficiency, | 91 |
| abstract_inverted_index.electricity | 45, 93, 166 |
| abstract_inverted_index.expenditure | 175 |
| abstract_inverted_index.integrating | 3 |
| abstract_inverted_index.operational | 52 |
| abstract_inverted_index.probability | 73 |
| abstract_inverted_index.regulations | 187 |
| abstract_inverted_index.sensitivity | 31 |
| abstract_inverted_index.Nonetheless, | 121 |
| abstract_inverted_index.demonstrated | 124 |
| abstract_inverted_index.highlighted. | 189 |
| abstract_inverted_index.simulations, | 36 |
| abstract_inverted_index.biorefineries | 8, 137 |
| abstract_inverted_index.characterised | 172 |
| abstract_inverted_index.computational | 90 |
| abstract_inverted_index.profitability | 41, 115 |
| abstract_inverted_index.significantly | 67 |
| abstract_inverted_index.opportunities, | 184 |
| abstract_inverted_index.lignocellulosic | 7 |
| cited_by_percentile_year | |
| countries_distinct_count | 3 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.2002407 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |