成果報告書詳細
管理番号20130000000623
タイトル*平成24年度中間年報 バイオマスエネルギー技術研究開発 戦略的次世代バイオマスエネルギー利用技術開発事業(次世代技術開発) 革新的噴流床ガス化とAntiーASF型FT合成によるバイオジェット燃料製造システムの研究開発
公開日2014/6/21
報告書年度2012 - 2012
委託先名三菱重工業株式会社 国立大学法人富山大学
プロジェクト番号P10010
部署名新エネルギー部
和文要約
英文要約Title: Development of Biojet Fuel Production Systems with Innovative Entrained Flow Gasifier and Anti-ASF FT Synthesis (FY2012-2013) FY2012 Annual Report

The commercialization of biomass to liquid (BTL) technology requires not only development of stand-alone processes but a total system solution. This R&D targets the development of an innovative biojet fuel production system. This R&D focuses on the development of entrained flow gasifier suitable for BTL and FT synthesis catalysts for biojet fuel with high selectivity and durability. This development is aimed at improving efficiency and reducing the cost of BTL systems, which are challenges in biomass energy consumption.
In FY2012 following items had been executed,
(1)Development of innovative entrained flow gasifier:
・Behavior of large biomass particle in gasifier had been studied to determine minimum superficial velocity in gasifier.
・Basic Study on thermochemical performances of herbaceous and wasted biomass had been carried out and showed that herbaceous biomass started to decompose at a slightly lower temperature, which suggested at low temperature (around 220-270deg-C), herbaceous biomass would soften to adhere to woody biomass and to make mixture.
(2)Demonstration of biojet fuel synthesis using bio-syngas:
・Preparation of test plant to demonstrate of biojet fuel synthesis using bio-syngas had been completed.
(3)Development of biojet fuel synthesis catalyst:
・FT reaction test had been carried out with using cobalt based catalyst to explore the effects of co-fed olefins on the product distribution of FT synthesis in order to search a kind of available olefin using for synthesis jet fuel via FT synthesis.
(4)Optimization of biojet fuel production system:
・Gasification process model had been constructed and properties of syngas could be predicted by using the model.
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