通过使用模糊分析层次流程,推进BtX,PtX,PBtX和eBtX设施的基于GIS的适用性分析
Marcel Dossow1, Mengxi Chen1, Hartmut Spliethoff1
1Technical University of Munich, Chair of Energy Systems, Boltzmannstr. 15, 85748, Garching b. München, Germany.
MethodsX
|February 24, 2025
概括
本研究引入了一种新的GIS和MCDA方法,以找到可持续燃料生产设施的最佳位置,如生物质到X和电力到X. 该方法系统地评估网站,帮助制定清洁能源解决方案的决策.
科学领域:
- 可持续能源系统 可持续能源系统
- 地理空间分析是什么
- 决策科学 决策科学 决策科学
背景情况:
- 迫切需要可持续的燃料生产.
- 目前的方法缺乏对新能源设施的系统空间优化.
- 生物质到X (BtX),电力到X (PtX) 和混合 (e-/PBtX) 技术需要仔细选择地点.
研究的目的:
- 开发和介绍一种新的方法,用于确定可持续燃料生产设施的最佳地点.
- 整合地理信息系统 (GIS) 和多标准决策分析 (MCDA) 进行定量位置适合性评估.
- 为BtX,PtX和e/PBtX的扩展提供一个系统的空间决策框架.
主要方法:
- 在CES-GIS-SAFAHP方法论中,GIS与模糊分析层次过程 (FAHP) 结合在一起.
- 地理空间数据被处理以创建特定标准的数据集 (例如,能源密度,可再生资源的可用性).
- 权重覆盖地图是使用FAHP与Fuzzy规范化生成的,与排除分析集成,以确定最佳的工厂位置.
主要成果:
- 制作一个最终的适合性地图,根据整体适合性指数突出显示最佳位置.
- 该方法提供了被分类的适用性和排除标准 (要求,基础设施,环境) 的列表.
- 提供了一个实用的,可复制的算法,用于指导用户通过网站选择过程.
结论:
- 拟议的方法提供了一个强大的,定量框架,用于空间优化,定位可持续燃料生产设施.
- 这种方法为参与扩大BtX,PtX和e/PBtX的政策制定者,行业和研究人员提供了有价值的见解.
- 综合的GIS-MCDA方法提高了可持续能源基础设施规划的效率和有效性.
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