A. Culaba, J. Juan, P. M. Ching, A. Mayol, E. Sybingco, A. Ubando
{"title":"Optimal Synthesis of Algal Biorefineries for Biofuel Production Based on Techno-Economic and Environmental Efficiency","authors":"A. Culaba, J. Juan, P. M. Ching, A. Mayol, E. Sybingco, A. Ubando","doi":"10.1109/HNICEM48295.2019.9072730","DOIUrl":null,"url":null,"abstract":"Biomass derived from microalgae is an emerging technology and attractive alternative source for biofuels. However, its exclusive production cannot be feasibly commercialized because of economic and environmental sustainability issues. The biorefinery concept allows microalgae to be efficiently converted into biofuels and other high-valued products, such as cosmetics, nutraceuticals, and pharmaceuticals. Nonetheless, this venture would require large capital investments that must be strategically scheduled across the lives of the investments, while keeping a reliable forecast of market growth. A multi-period multi-objective mixed integer non-linear programming (MINLP) model is proposed in this study to determine optimal investment schedule and operational decisions that would simultaneously maximize the net present value (NPV) and minimize the greenhouse gas (GHG) emissions of an algal biorefinery. An illustrative case study and scenario analyses demonstrate the validity and the capabilities of the proposed model.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"4 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HNICEM48295.2019.9072730","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Biomass derived from microalgae is an emerging technology and attractive alternative source for biofuels. However, its exclusive production cannot be feasibly commercialized because of economic and environmental sustainability issues. The biorefinery concept allows microalgae to be efficiently converted into biofuels and other high-valued products, such as cosmetics, nutraceuticals, and pharmaceuticals. Nonetheless, this venture would require large capital investments that must be strategically scheduled across the lives of the investments, while keeping a reliable forecast of market growth. A multi-period multi-objective mixed integer non-linear programming (MINLP) model is proposed in this study to determine optimal investment schedule and operational decisions that would simultaneously maximize the net present value (NPV) and minimize the greenhouse gas (GHG) emissions of an algal biorefinery. An illustrative case study and scenario analyses demonstrate the validity and the capabilities of the proposed model.