{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/122230"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/122230","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"The design of a bioenergy potential map and a GIS-enabled optimization model for biofuel production in India","abstract":"India has a remarkably large inventory of biomass, but the operation of biorefineries has been difficult due to the uncertainty in biomass availability and the lack of biomass supply chain management in the industry. To help biorefinery operators make strategic decisions, this study develops a model that optimizes and evaluates the economic viability of bioenergy/biofuel production technologies in India. To enhance the accuracy of the simulation, bioenergy potential is mapped out using geospatial information system, and biomass transportation distances are calculated using geospatial network analysis. The optimization model is built as a mixed integer linear programming problem to solve for the optimal locations, number and scale of the biorefinery, and biomass flows to it. Biosynthetic natural gas (bioSNG) production technology, GoBiGas, is used to test the model. The levelized cost of bioSNG and the ensuing cost sensitivity analysis concludes that this particular technology configuration is not sustainably profitable in India, but a less capital intensive technology might be able to demonstrate otherwise.","abstract_html":"India has a remarkably large inventory of biomass, but the operation of biorefineries has been difficult due to the uncertainty in biomass availability and the lack of biomass supply chain management in the industry. To help biorefinery operators make strategic decisions, this study develops a model that optimizes and evaluates the economic viability of bioenergy/biofuel production technologies in India. To enhance the accuracy of the simulation, bioenergy potential is mapped out using geospatial information system, and biomass transportation distances are calculated using geospatial network analysis. The optimization model is built as a mixed integer linear programming problem to solve for the optimal locations, number and scale of the biorefinery, and biomass flows to it. Biosynthetic natural gas (bioSNG) production technology, GoBiGas, is used to test the model. The levelized cost of bioSNG and the ensuing cost sensitivity analysis concludes that this particular technology configuration is not sustainably profitable in India, but a less capital intensive technology might be able to demonstrate otherwise.","abstract_has_math":false,"creators":["Yan, YanS.M.Massachusetts Institute of Technology."],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Mechanical Engineering","school":null,"contributors":[],"advisors":["Ahmed Ghoniem."],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019","date_published":"2019","updated_at":"2026-07-22T22:20:44Z","subjects":["Mechanical Engineering."],"languages":["eng"],"rights":["MIT theses are protected by copyright. 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