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Compromises In Energy Policy-using Fuzzy Optimization In An Energy Systems Model

机译:使用能源系统模型中的模糊优化折衷能源政策

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Over the last year in Germany a great many political discussions have centered around the future direction of energy and climate policy. Due to a number of events related to energy prices, security of supply and climate change, it has been necessary to develop cornerstones for a new integrated energy and climate policy. To supplement this decision process, model-based scenarios were used. In this paper we introduce fuzzy constraints to obtain a better representation of political decision processes, in particular, to find compromises between often contradictory targets (e.g. economic, environmentally friendly and secure energy supply). A number of policy aims derived from a review of the ongoing political discussions were formulated as fuzzy constraints to explicitly include trade-offs between various targets. The result is an overall satisfaction level of about 60% contingent upon the following restrictions: share of energy imports, share of biofuels, share of CHP electricity, CO_2 reduction target and use of domestic hard coal. The restrictions for the share of renewable electricity, share of renewable heat, energy efficiency and postponement of nuclear phase out have higher membership function values, i.e. they are not binding and therefore get done on the side.
机译:去年在德国,许多政治讨论都围绕能源和气候政策的未来方向展开。由于与能源价格,供应安全和气候变化有关的许多事件,有必要为新的综合能源和气候政策制定基石。为了补充此决策过程,使用了基于模型的方案。在本文中,我们引入了模糊约束条件,以更好地表示政治决策过程,特别是在经常相互矛盾的目标(例如经济,环境友好和安全的能源供应)之间寻找折衷方案。从对正在进行的政治讨论进行回顾得出的许多政策目标被表述为模糊约束,以明确包括各种目标之间的权衡。结果是总的满意水平约为60%,取决于以下限制:能源进口份额,生物燃料份额,CHP电力份额,CO_2减排目标和家用硬煤的使用。对可再生电力份额,可再生热量份额,能源效率和核淘汰推迟的限制具有较高的隶属函数值,即它们没有约束力,因此可以从侧面进行。

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