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A generic framework for power system flexibility analysis using cooperative game theory

机译:基于合作博弈的电力系统灵活性分析通用框架

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Electricity grid infrastructures provides valuable flexibility in power systems with high shares of variable supply due to its ability to distribute low-cost supply to load centers (spatial), in addition to interlinking a variety of supply and demand characteristics that potentially offset each others negative impact on system balance (temporal). In this paper, we present a framework to investigate the benefits of alternative flexibility providers, such as fast-ramping gas turbines, hydropower and demand side management, by using a generation and transmission capacity expansion planning model. We demonstrate our findings with a multinational case study of the North Sea Offshore Grid with an infrastructure typology from year 2016 and operational data for year 2030 considering a range of renewable capacity levels spanning from 0% to 100%. First, we show how different flexibility providers are allocated geographically by the model. Second, operational cost savings are quantified per incremental unit of flexible capacity. Finally, we present a way to rank different flexibility providers by considering their marginal contribution to aggregate cost savings, reduced CO2 emissions, and increased utilization of renewable energy sources in the system. The Shapley Value from cooperative game theory allows us to assess the latter benefits accounting for all possible sequences of technology deployment, in contrast to traditional approaches. The presented framework could help to gain insights for energy policy designs or risk assessments.
机译:电网基础设施除了可以将可能相互抵消的负面影响的各种供需特征相互关联之外,还具有将低成本电力分配到负荷中心(空间)的能力,从而为可变电力供应较高的电力系统提供了宝贵的灵活性。在系统平衡(时间)上。在本文中,我们提出了一个框架,该框架通过使用发电和输电容量扩展规划模型来研究替代灵活性提供商的利益,例如快速升温的燃气轮机,水电和需求侧管理。我们通过对北海近海电网的跨国案例研究证明了我们的发现,该案例研究了2016年的基础设施类型以及2030年的运营数据,其中考虑了范围从0%到100%的可再生能源水平。首先,我们展示了模型如何在地理上分配不同的灵活性提供者。其次,运营成本的节省是按弹性容量的增量单位量化的。最后,我们提出一种方法,通过考虑它们对总成本节省,二氧化碳排放量减少以及系统中可再生能源利用率提高的边际贡献,对不同的灵活性提供商进行排名。合作博弈理论的Shapley值使我们能够评估与传统方法相比考虑了技术部署的所有可能顺序的后一种利益。提出的框架可以帮助获得有关能源政策设计或风险评估的见识。

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