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A power-flow emulator approach for resilience assessment of repairable power grids subject to weather-induced failures and data deficiency

机译:一种潮流仿真器方法,用于评估因天气原因导致的故障和数据不足的可修复电网的弹性

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摘要

A generalised uncertainty quantification framework for resilience assessment of weather-coupled, repairable power grids is presented. The framework can be used to efficiently quantify both epistemic and aleatory uncertainty affecting, grid-related and weather-related factors. The power grid simulator has been specifically designed to model interactions between severe weather conditions and grid dynamic states and behaviours, such as weather-induced failures or delays in components replacements. A resilience index is computed by adopting a novel algorithm which exploits a vectorised emulator of the power-flow solver to reduce the computational efforts. The resilience stochastic modelling framework is embedded into a non-intrusive generalised stochastic framework, which enables the analyst to quantify the effect of parameters imprecision. A modified version of the IEEE 24 nodes reliability test system has been used as representative case study. The surrogate-based model and the Power-Flow-based model are compared, and the results show similar accuracy but enhanced efficiency of the former. Global sensitivity of the resilience index to increasing imprecision in parameters of the probabilistic model has been analysed. The relevance of specific weather/grid uncertain factors is highlighted by global sensitivity analysis and the importance of dealing with imprecision in the information clearly emerges.
机译:提出了用于天气耦合可修复电网弹性评估的广义不确定性量化框架。该框架可用于有效地量化影响网格相关和天气相关因素的认知和偶然不确定性。电网仿真器经过专门设计,可以对恶劣天气条件与电网动态状态和行为(如天气引起的故障或组件更换延迟)之间的相互作用进行建模。通过采用一种新颖的算法来计算弹性指数,该算法利用了潮流求解器的矢量化仿真器来减少计算量。弹性随机建模框架被嵌入到非侵入式广义随机框架中,这使分析人员能够量化参数不精确性的影响。 IEEE 24节点可靠性测试系统的修改版已用作代表性案例研究。比较了基于代理模型和基于功率流模型,结果显示出相似的准确性,但前者的效率有所提高。弹性指数对概率模型参数不精确度的整体敏感性已得到分析。全球敏感性分析强调了特定天气/电网不确定因素的相关性,并且清楚地显示了处理信息不精确性的重要性。

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