Multi objective optimization of ethanol production based on regional resource availability

Production of lignocellulosic biofuels must respect the regional water availability constraints, while simultaneously balancing the social and economic objectives. This work has proposed a multi-objective optimization model to design regional biomass to energy system incorporating these factors. The goal is to design a bioenergy system that is constrained by district level land availability, regional water availability, and competing water demands. The allocation of agricultural land to selected crops is the key decision. Additionally, the number of biorefineries, their locations, and their feedstock procurement strategies are also optimised. Four different objectives, namely, minimization of ethanol cost, minimization of water footprint of ethanol, minimization of irrigation water, and maximization of farmers' profit, are considered for meeting a specified monthly ethanol demand. The resulting multi-objective mixed-integer linear programming problem was applied to a case study of 33 districts in Maharashtra, India. The problem was solved using the epsilon-constraint method where all objectives, except one, were used as constraints. Results indicated a significant trade-off between ethanol cost and irrigation water requirement. Sorghum, wheat and cotton were the prominent crops recommended by the model at various regions in the Pareto front, while Jalna, Kolhapur and Pune were among the most frequently selected locations for setting up biorefineries. Ethanol cost varied from (sic)47/l ($0.63/l) to (sic)60/l ($0.80/l), while water footprint varied from 665 l/l to 301 l/l, irrigation water varied from 43m(3)/ha to 2768m(3)/ha, and farmers' profit from (sic)21059/ha ($281/ha) to (sic)6825/ha ($91/ha). (C) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Automated summary

This study proposed a multi-objective optimization model to design lignocellulosic biofuels production system, considering factors such as regional water availability, land availability, and competing water demands. The results showed a significant trade-off between ethanol cost and irrigation water requirement, recommending specific crops and biorefinery locations in different regions.