Wind farm location determination by using a two-phased fuzzy decision-making methodology based on fused data with a real case application

IF 2 Q4 ENERGY & FUELS
A. Karaşan, Murat Çolak, Ayşenur Budak, I. Kaya
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引用次数: 1

Abstract

ABSTRACT Location selection for power plants operating with renewable energy is critical, and their locations directly affect performance and productivity. In this paper, a novel two-phased MCDM methodology based on z-fuzzy numbers with a better modelling capability by defining a confidence degree in decision-making problems is proposed to evaluate alternative locations for wind farm installation in Marmara Region, Turkey. As a result, while Çanakkale has been selected as the most suitable city, the alternative location named Biga has been determined as the most appropriate location in this city for wind farm installation. In addition, sensitivity and comparative analyses have been conducted to check the flexibility of the given decisions and verification of the weights of the criteria, respectively.
基于融合数据的两阶段模糊决策方法在风电场选址中的应用
摘要:可再生能源电厂的选址至关重要,其选址直接影响电厂的性能和生产率。本文提出了一种新的两阶段MCDM方法,该方法基于z-模糊数,通过定义决策问题的置信度,具有更好的建模能力,用于评估土耳其马尔马拉地区风电场安装的备选地点。因此,虽然Çanakkale被选为最合适的城市,但另一个名为Biga的地点被确定为该城市最适合安装风力发电场的地点。此外,还分别进行了敏感性分析和比较分析,以检查所作决定的灵活性和核查标准的权重。
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来源期刊
CiteScore
5.70
自引率
3.20%
发文量
52
期刊介绍: Engineering and sustainable development are intrinsically linked. All capital plant and every consumable product depends on an engineering input through design, manufacture and operation, if not for the product itself then for the equipment required to process and transport the raw materials and the final product. Many aspects of sustainable development depend directly on appropriate and timely actions by engineers. Engineering is an extended process of analysis, synthesis, evaluation and execution and, therefore, it is argued that engineers must be involved from the outset of any proposal to develop sustainable solutions. Engineering embraces many disciplines and truly sustainable solutions are usually inter-disciplinary in nature.
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