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Optimizing the bioenergy industry infrastructure: Transportation networks and bioenergy plant locations

机译:优化生物能源行业的基础设施:交通网络和生物能源工厂的位置

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摘要

In the context of combating climate change and maintaining energy security, ambitious bioenergy development projects in emerging economies face considerable challenges, for example an overburdened bioenergy industry infrastructure due to the growing demand for bioenergy products. There are abundant studies on optimizing the bioenergy industry infrastructure. However, they fail to comprehensively simulate the interactions among the predominant actors of the infrastructure, especially the bioenergy plant operators in emerging economies. To fill this research gap, We develop a new dynamic agent -based model of optimized bioenergy industry infrastructure. from the perspective of bioenergy plant operators. We then apply the model to Jiangsu Province of China to simulate the coordination of two types of bioenergy plants and project the optimal distribution of these plants and their corresponding transportation networks for the year of 2030. The model results suggest locating bioenergy plants closer to bioenergy feedstock source regions rather than to bioenergy products consumption sites, an answer to the classical facility location problem. A welfare analysis based on the extended model indicates that the biomass densification process aiming at mitigating the growing transport volumes incurred by the delivery of bulky bioenergy feedstock is not economically profitable in our case region. The experiences from this region further show that for emerging economies, a successful bioenergy industry infrastructure needs to take the benefits of smallholder farmers into consideration. (C) 2017 Elsevier Ltd. All rights reserved.
机译:在应对气候变化和维持能源安全的背景下,新兴经济体中雄心勃勃的生物能源开发项目面临巨大挑战,例如,由于对生物能源产品的需求不断增长,生物能源行业的基础设施负担过重。关于优化生物能源产业基础设施的研究很多。但是,他们无法全面模拟基础设施主要参与者之间的互动,尤其是新兴经济体中的生物能源工厂运营商之间的互动。为了填补这一研究空白,我们开发了一种基于动态代理的新型模型,用于优化生物能源行业的基础设施。从生物能源工厂运营商的角度来看。然后,我们将该模型应用到中国江苏省,以模拟两种类型的生物能源工厂的协调,并预测这些植物及其相应的运输网络在2030年的最佳分布。该模型结果建议将生物能源工厂的位置更靠近生物能源原料源区域,而不是生物能源产品的消费地点,这是经典设施选址问题的答案。基于扩展模型的福利分析表明,旨在减轻因散装生物能源原料的输送而引起的运输量增长的生物质致密化过程在我们的案例区域内没有经济上的利润。该地区的经验进一步表明,对于新兴经济体而言,成功的生物能源产业基础设施需要考虑小农的利益。 (C)2017 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Applied Energy》 |2017年第15期|247-261|共15页
  • 作者单位

    Univ Hamburg, Inst Geog, Res Grp Climate Change & Secur, Ctr Earth Syst Res & Sustainabil, D-20144 Hamburg, Germany|Inst Adv Studies Sci Technol & Soc, A-8010 Graz, Austria;

    Univ Hamburg, Res Unit Sustainabil & Global Change, Ctr Earth Syst Res & Sustainabil, D-20144 Hamburg, Germany;

    Univ Hamburg, Inst Geog, Res Grp Climate Change & Secur, Ctr Earth Syst Res & Sustainabil, D-20144 Hamburg, Germany;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Bioenergy; Facility location; Agent-based model; Optimization; China;

    机译:生物能源;设施选址;基于Agent的模型;优化;中国;

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