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Research on the influence factors of ubiquitous power Internet of things for promoting consumption of wind power based on fuzzy G1-ISM in China

机译:基于模糊G1 ism的风电互联网互联网互联网影响因素研究

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In the last decade, the scale and speed of development for wind power in China presented an explosive growth and has been maintaining a leading position worldwide. However, rapid development, with addition of the nature of clean energy itself, is followed by the problem of energy consumption such as wind curtailment. To improve the energy efficiency, a new pattern of wind power generation, namely the non-grid-connected wind power, is gradually accessible to the public. At the same time, proposes a novel concept of ubiquitous power Internet of things (UPIoTs) to improve the energy-using environment and quality. In the context of above proposal, to research how UPIoTs promotes the consumption of wind power especially has become a crucial task. The purpose of this paper is to identify influence factors through literature review and expert interview on the basis of relationship between the referenced two. During the process of exploring effects among factors, the improved interpretative structural modeling (ISM) coupled with fuzzy order relation analysis method (fuzzy G1 method) is constructed and adopted to make up for the shortcomings of traditional method. According to the results, three factors are considered as the most influential and some suggestions are given from these three aspects, aiming at making a contribution to the solutions in theory and in practice.
机译:在过去的十年中,中国风电发展的规模和速度呈现出爆炸性的增长,并一直在全球的领先地位。然而,随着清洁能源本身的性质,快速发展,随后是风缩小的能耗问题。为了提高能源效率,公众逐渐访问了一种新的风力发电模式,即非网路上的风电。与此同时,提出了一部普遍存在的电源互联网(Upiots)的新颖概念,以改善能源的环境和质量。在上述建议的背景下,研究Ubiots如何促进风力的消费,特别是一项至关重要的任务。本文的目的是通过基于引用二之间的关系来确定通过文献审查和专家面试的影响因素。在探索因子之间的探索过程中,构建和采用了与模糊阶关系分析方法(模糊G1方法)耦合的改进的解释结构建模(ISM)以弥补传统方法的缺点。根据结果​​,三个因素被认为是最有影响力的,这三个方面得到了一些建议,旨在在理论和实践中对解决方案做出贡献。

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