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Suitability modeling and sensitivity analysis for biomass energy facilities in Turkey

机译：土耳其生物质能源设施的适用性建模与敏感性分析

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摘要

Nowadays, problems relating to the inadequacy of energy resources are emerging, due to fast population growth and inevitable urban sprawl. Renewable energy resources are of vital importance in order to overcome these problems that endanger countries in terms of economic, social, and environmental factors. The determination of suitable facility locations is a key matter to solve, in order to effectively exploit biomass energy potential. This paper proposes an approach to biomass facility location that integrates open-source geographic information systems (GIS), fuzzy logic, and a best worst method (BWM) solution, which is a newly developed multi-criteria decision-making (MCDM) method to address optimal facility location. Suitable locations take different criteria into consideration, including potential biomass amount (e.g., agricultural and animal wastes), slope, and distances to roads and water bodies. By utilizing MCDM, the most critical criterion can be determined. Moreover, the paper demonstrates that fuzzy logic allows intermediate values for suitability criteria and is preferable to Boolean logic. The proposed approach is illustrated using all cities of Turkey as an empirical case study. Four specific regions that greatly have highly suitable areas are presented. Sensitivity analysis shows that different agendas such as economic cost and social impact might change the suitability results, specifically in areas of the highly suitable class. These results are most strongly affected by potential biomass amount, population density, and distances to roads and settlements.
机译：如今，由于人口快速增长和不可避免的城市蔓延，出现了与能源资源不足的问题。可再生能源资源至关重要，以克服经济，社会和环境因素方面危及国家的这些问题。确定合适的设施位置是解决的关键问题，以有效利用生物量能源潜力。本文提出了一种对生物量设施位置的方法，它集成了开源地理信息系统（GIS），模糊逻辑和最佳的最差方法（BWM）解决方案，这是一种新开发的多标准决策（MCDM）方法地址最佳设施位置。适用的位置考虑不同的标准，包括潜在的生物质量（例如，农业和动物废物），坡度和距离道路和水体的距离。通过利用MCDM，可以确定最关键的标准。此外，本文证明了模糊逻辑允许适合性标准的中间值，并且优选布尔逻辑。使用土耳其的所有城市作为经验案例研究说明了所提出的方法。提供了四个特定的区域，极大地具有高度合适的区域。敏感性分析表明，经济成本和社会影响等不同议程可能会改变适当的结果，特别是在高度合适的课程中。这些结果受到潜在的生物质量，人口密度和道路和定居点的距离最强烈的影响。

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