期刊
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
卷 98, 期 -, 页码 393-406出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2018.09.017
关键词
Cellulosic ethanol; Geographic production and consumption; Biorefinery; Ghana
资金
- Rackham Global Engagement Program at the University of Michigan
Owing to the high availability of crop residues in Ghana, ethanol produced from cellulosic feedstock provides an opportunity to achieve energy security without competing with food crops. This study applied methods to identify the best locations in Ghana for biorefineries with 100 ML and 50 ML annual production capacity for cellulosic ethanol, by minimizing transportation costs involved in the biomass residue feedstock collection and distribution of the ethanol produced by the biorefinery. The potential for ethanol production in the 10 regions of Ghana from 11 major crop residues was determined. Brong Ahafo and Eastern were identified as the regions with the highest ethanol production potential from single crop residues (with ethanol production potential of > 120 ML/yr), and residue from maize crop was identified as the biomass with the highest potential as source material. Two ethanol distribution scenarios were considered assuming the ethanol would be mixed with gasoline to produce an E10 fuel blend (10% ethanol by volume). In one scenario, all ethanol from the biorefineries was transported to Tema and then distributed using the existing gasoline infrastructure. In the second scenario, ethanol was delivered from the biorefineries directly to the major demand cities. Total transportation costs were used to identify which of nine candidate locations for the biorefineries and which ethanol distribution scenario led to the lowest costs. The results showed the best configuration to meet supply-and demand-side constraints was to use three biorefineries of 50 ML/yr capacity each to supply individual demand locations across the country, and biorefineries located in Koforidua in Eastern and Sunyani in Brong Ahafo led to the lowest transportation costs regardless of distribution scenario. The recommended biorefinery locations showed low sensitivity to important input assumptions, indicating a low risk to the development of biorefineries at Koforidua and Sunyani based on minimizing transportation costs.
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