Spatio-temporal assessment of the impact of intensive palm oil-based bioenergy deployment on cross-sectoral energy decarbonization
Although aspects of long-term planning are commonly taken into account in current analyses of bioenergy policy scenarios, representations of the bioenergy supply chain are often spatially aggregated. Multiple questions such as where, when, and how bioenergy is deployed have thus not been sufficientl...
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| Main Authors: | , , , , |
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| Format: | Article |
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Elsevier Ltd.
2021
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/94837/ http://dx.doi.org/10.1016/j.apenergy.2021.116460 |
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| Summary: | Although aspects of long-term planning are commonly taken into account in current analyses of bioenergy policy scenarios, representations of the bioenergy supply chain are often spatially aggregated. Multiple questions such as where, when, and how bioenergy is deployed have thus not been sufficiently addressed within a single modeling framework. Moreover, techno-economic models that can capture the dependencies of bioenergy supply chain variables among end-use sectors still need to be explored. The present research connects these gaps by presenting the development of a spatio-temporal techno-economic optimization model for cross-sectoral bioenergy policy evaluations under high spatial resolution and long-term temporal resolution. The research recognizes not only the need for energy decarbonization, but also the importance of improving resource efficiency in the palm oil industry, in this case, Malaysia's palm oil bioenergy industry. The findings highlight the need for multi-sectoral collaboration between the energy sectors to deliver cost-optimal energy decarbonization at the national scale. This is represented by the substitution of up to 30%, 27%, and 12% of the energy demands in the power, heat, and transport sectors with bioenergy, respectively. The conflict between policy targets was also highlighted, namely, that new policies prioritizing bioenergy in the power and transport sectors reduce CO2 more effectively than policies targeting CO2 reduction alone, however, requiring up to 37% more cost in meeting the CO2 reduction commitment. The findings also outline the requirement of co-locating bioenergy production facilities with the existing facilities (e.g., agricultural mills, coal plants) and extending the existing infrastructure network to deliver the bioenergy capacities needed to meet the policy targets. |
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