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An intuitionistic fuzzy multi-criteria framework for large-scale rooftop PV project portfolio selection: Case study in Zhejiang, China

机译:大规模屋顶光伏项目组合选择的直觉模糊多准则框架:以中国浙江为例

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摘要

Selecting a rational large-scale rooftop photovoltaic (LSR-PV) project portfolio is critical to the realization of long-term strategy objectives for PV enterprises. Difficulties related to LSR-PV project portfolio selection result from factors including uncertainties of decision-making environment, various properties of evaluation attributes and interactions between projects. However, the existing researches on portfolio selection have not solved these problems well. In this work, combining of fuzzy multi-attribute decision making and fuzzy multi-objective programming, an integrated framework is proposed to address these issues simultaneously. First, the assessment values of attributes, objective functions and constrains all take the form of triangular intuitionistic fuzzy numbers (TIFNs) to fully describe the uncertainties inherent to LSR-PV project portfolio selection. Later, the weights of attributes determined by Analytic Hierarchy Process (AHP) are incorporated within PROMETHEE II method to sort the LSR-PV project alternatives by selecting preference functions and setting parameters for each attribute. Then, a fuzzy 0-1 programming model is formulated and the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) algorithm is introduced to capture an optimal-Pareto set under objectives of benefit maximization and installed capacity maximization. Finally, to validate the effectiveness of the proposed framework, a case study of Zhejiang province is conducted and a comparative analysis is carried out. (C) 2017 Elsevier Ltd. All rights reserved.
机译:选择合理的大型屋顶光伏(LSR-PV)项目组合对于实现光伏企业的长期战略目标至关重要。与LSR-PV项目组合选择有关的困难是由以下因素造成的:决策环境的不确定性,评估属性的各种属性以及项目之间的相互作用。但是,现有的投资组合选择研究并不能很好地解决这些问题。在这项工作中,将模糊多属性决策与模糊多目标规划相结合,提出了一个同时解决这些问题的集成框架。首先,属性,目标函数和约束的评估值均采用三角直觉模糊数(TIFN)的形式,以充分描述LSR-PV项目组合选择固有的不确定性。后来,通过PROMETHEE II方法将由层次分析法(AHP)确定的属性权重合并在一起,以通过选择首选项函数和为每个属性设置参数来对LSR-PV项目替代项进行排序。然后,建立了模糊0-1规划模型,并引入了非支配排序遗传算法-II(NSGA-II)算法来捕获以收益最大化和装机容量最大化为目标的最优Pareto集。最后,为验证所提出框架的有效性,以浙江省为例进行了比较分析。 (C)2017 Elsevier Ltd.保留所有权利。

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