Abstract
Blockchain technology is widely concerned, and its related applications can promote the process of smart cities and sustainable society. However, while mining the potential application scenarios in power trading, we must recognize the barriers, help it survive the hype stage, and promote its healthy development and technology landing. For the first time, hesitant fuzzy linguistic term set and K-mediods clustering algorithm are used to improve the decision-making trial and evaluation laboratory (DEMATEL) method, and the obstacle analysis model of the applied scene is constructed. Compared with the conventional DEMATEL method, the collection of evaluation information is more flexible and closer to reality. Besides, the classification of obstacle factors is more scientific and there can be more than two categories for effect degree. Firstly, thirteen barriers to its application in power trading are identified; at the same time, six specific application scenarios are summarized and analyzed. Then, a detailed discussion is conducted on each scenario: The quantification of the influence degree among obstacles, the classification and qualitative of the influence degree, and the causal mechanism analysis. The key obstacles identified can be used to guide practice. Finally, strategic solutions and policy recommendations are given to remove or alleviate these obstacles.
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