Using mixed integer linear programming to integrate biofuel into Ghana’s petroleum supply chain for sustainable energy transition
Akyene Tetteh & Gideon Fraser
What the paper says
Ghana addresses its energy challenges by promoting policies to diversify the energy mix, reduce reliance on imported petroleum, and promote its green economy. Ghana’s Bioenergy Policy underscores this transition by promoting biofuel integration into Ghana’s petroleum supply chain to diversify the energy mix and reduce reliance on imported petroleum. However, the lack of robust infrastructure for biomass-to-biofuel supply chains presents a significant challenge. This research aims to address this gap by integrating biofuels into the existing petroleum supply chain and optimizing the distribution taking into account the unique infrastructural, economic, and logistical challenges. The study used a mixed integer linear programming (MILP) model to model the integration of biofuel into Ghana’s petroleum supply chain and subsequently analyzed different production scenarios using statistical data. The simulation results suggest that to achieve the targeted 20% biofuel integration goal, the country needs to produce up to 465,000 Mt of bioethanol and 528,000 Mt of biodiesel. Blending biofuels with fossil fuels can promote Ghana’s energy sustainability and security, job creation, and economic benefits, including incurring an opportunity cost of US$845 million from fossil fuel imports annually. Hence, strategic planning and investment in infrastructure are essential to leverage the benefits of biofuel and support Ghana’s sustainable energy transition. The research brings clarity to Ghana’s agenda of integrating 20% biofuels into Ghana’s petroleum supply chain by 2030, indicating the benefits and the essential investment required.
2 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.25 × 0.4 = 0.10 |
| M · momentum | 0.55 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.