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Which energy mix for the UK (United Kingdom)? An evolutive descriptive mapping with the integrated GAIA (graphical analysis for interactive aid)–AHP (analytic hierarchy process) visualization tool

机译:英国(英国)的哪种能源组合?使用集成GaIa(交互式辅助图形分析)-aHp(分析层次结构过程)可视化工具的演化描述性映射

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摘要

Although Multi-Criteria Decision Making methods have been extensively used in energy planning, their descriptive use has been rarely considered. In this paper, we add an evolutionary description phase as an extension to the AHP method that helps policy makers to gain insights into their decision problems. The proposed extension has been implemented in an open-source software that allows the users to visualise the difference of opinions within a decision process, and also the evolution of preferences over time. The method was tested in a two-phase experiment to understand the evolution of opinions on energy sources. Participants were asked to provide their preferences for different energy sources for the next twenty years for the United Kingdom. They were first asked to compare the options intuitively without using any structured approach, and then were given three months to compare the same set of options after collecting detailed information on the technical, economic, environmental and social impacts created by each of the selected energy sources. The proposed visualization method allows us to quickly discover the preference directions, and also the changes in their preferences from first to second phase. The proposed tool can help policy makers in better understanding of the energy planning problems that will lead us towards better planning and decisions in the energy sector.
机译:尽管多标准决策方法已广泛用于能源规划中,但很少考虑使用其描述性方法。在本文中,我们增加了进化描述阶段,作为AHP方法的扩展,可帮助决策者深入了解其决策问题。提议的扩展已在开源软件中实现,该软件允许用户可视化决策过程中意见的差异以及偏好随时间的演变。在两个阶段的实验中对该方法进行了测试,以了解能源观点的演变。要求与会者提供联合王国在未来20年内对不同能源的偏好。首先要求他们在不使用任何结构化方法的情况下直观地比较这些选项,然后在收集有关每种选定能源所产生的技术,经济,环境和社会影响的详细信息后,给予三个月的时间来比较同一组选项。所提出的可视化方法使我们能够快速发现偏好方向,以及它们从第一阶段到第二阶段的偏好变化。拟议中的工具可以帮助决策者更好地理解能源规划问题,这些问题将使我们朝着能源部门的更好规划和决策迈进。

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