IIT Hyderabad researchers use novel method to study biofuels

IIT Hyderabad researchers use novel method to study biofuels

HYDERABAD [Maha Media]: The Indian Institute of Technology Hyderabad (IIT-H) on Thursday said its researchers are using computational methods to understand the factors and impediments in incorporating biofuels into the fuel sector in India.

This work has been spurred by the increasing need to replace fossil fuels by bio-derived fuels, which, in turn, is driven by the dwindling fossil fuel reserves all over the world, and pollution issues associated with the use of fossil fuels.

The model developed by the IIT team has shown that in the area of bioethanol integration into mainstream fuel use, the production cost is the highest (43 per cent) followed by import (25 per cent), transport (17 per cent), infrastructure (15 per cent) and inventory (0.43 per cent) costs.

The model, published in Journal of Cleaner Production, has also shown that feed availability to the tune of at least 40 per cent of the capacity is needed to meet the projected demands.

A unique feature of this work is that the framework considers the revenue generation not only as an outcome of sales of the biofuel, but also in terms of carbon credits via greenhouse gas emission savings throughout the project lifecycle.

"In India, biofuels generated from non-food sources is the most promising source of carbon-neutral renewable energy," Dr. Kishalay Mitra, Associate Professor, Department of Chemical Engineering, IIT Hyderabad, said in a statement.

"These second-generation sources include agricultural waste products such as straw, hay and wood, among others, that do not intrude upon food sources," Mitra added.

According to the Institute, biofuel technologies are evolving in India. The design and implementation of technological, regulatory and policy approaches and pricing strategy of biofuels depend on a deep understanding of the supply chain network.

Models such as those developed at IIT Hyderabad allow the society to understand the effects of uncertainty in the network parameters on the demand-supply dynamics and can help policymakers devise and revise strategies to meet the future demands of biofuels.

"We use Machine Learning techniques to understand the supply chain network," said Kapil Gumte, Research Scholar, IIT Hyderabad.

"Machine learning is a branch of Artificial Intelligence in which, the computer learns patterns from available data and updates automatically to produce an understanding of the system and predictions of the future," Gumte added.
 

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