Journal
ENERGY CONVERSION AND MANAGEMENT
Volume 225, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2020.113345
Keywords
Waste animal fat; Non-edible feedstock; Sustainable biodiesel supply chain; Robust possibilistic programming; Social responsibility
Categories
Funding
- National Research Foundation of Korea (NRF) - Korea Government (MSIT) [NRF2020R1F1A1064460]
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The ever-increasing energy demand and harmful environmental and social impacts instigated by fossil fuels have led to the development of sustainable energy resources. Biodiesel has been introduced as an alternative owing to its wide commercial applications. It can be produced from various types of biomass including vegetable oil, used cooking oil, and animal fat. Of these, animal fat is a promising option because of its low cost and easy availability. For a speedy transition toward large-scale commercially viable biodiesel production, the efficient design of a biodiesel supply chain is very important. Moreover, because biodiesel supply chain (SC) design decisions directly influence social and environmental aspects, hence SC optimization within the sustainability paradigm is necessary. This research proposes a waste-animal-fat-based biodiesel SC optimization model that minimizes environmental impact and SC cost while maximizing social wellbeing. The complex and dynamic environment of biodiesel production brings a high level of uncertainty, which compromises the effectiveness of SC decisions; thus, a modified robust possibilistic chance-constrained programming solution methodology is developed. To validate the proposed model and solution methodology, a computational analysis of a case study is performed. The results demonstrate that by paying 1.13% higher costs, a desirable level of social and environmental protection can be achieved for the proposed supply chain. It is also found that with an increase of 5% in the economic objective, 6% increase in the environmental objective, and 7% decrease in the social objective, the risk of epistemic uncertainty can be completely ruled out. Further, from the numerical analysis it is inferred that among all tiers of biodiesel SC, the decisions of the biorefinery tier play a crucial role in achieving sustainable development goals. Furthermore, a higher priority of economic and environmental objectives makes the SC decisions more centralized, whereas a higher priority of the social objective makes them more decentralized. The proposed model can be useful to investors and policymakers involved in biodiesel production and distribution.
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