Day-ahead preventive scheduling of power systems during natuaral hazards via stochastic optimization
Day-ahead preventive scheduling of power systems during natuaral hazards via stochastic optimization
复制标题
通过随机优化在自然灾害期间对电力系统进行日前预防性调度
DOI：
10.1109/pesgm.2017.8274453
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Ge Ou
中科院分区：
文献类型：
--
作者：
M. Sahraei;Ge Ou
可预测的与天气有关的自然灾害与美国大部分停电有关。由于传统的可靠性标准不是针对这种情况设计的，因此它们不能保证在这种极端事件期间可靠地输送电力。本文提出了一个两阶段模型，在自然灾害期间的电力系统预防性操作。在第一阶段，基于结构易损性分析计算输电塔的失效概率。然后，通过第一阶段中进行的分析生成故障情景及其概率。在第二阶段，故障场景及其概率被用于随机优化框架中，以显式地建模传输元件的可能故障。IEEE 118节点系统的仿真研究表明，该方法可以有效地消除网络违规通过预防性调整的发电调度。结果还表明，再调度成本是不显着的，相比切负荷的潜在后果。
Predictable weather-related natural hazards are tied to a significant portion of the blackouts in the United States. Since conventional reliability standards are not designed for such conditions, they fail to guarantee reliable delivery of power during such extreme events. This paper proposes a two-stage model for preventive operation of power systems during a natural hazard. At the first stage, failure probability of transmission towers is calculated based on fragility analysis of the structure. The failure scenarios and their probabilities are, then, generated through the analysis conducted in the first stage. At the second stage, the failure scenarios and their probabilities are used in stochastic optimization framework to explicitly model the likely failure of transmission elements. Simulation studies, carried out on IEEE 118-bus system, show that the proposed method can effectively eliminate network violations through preventive adjustment of generation dispatch. The results also show that the redispatch cost is not significant, compared to the potential consequences of shedding load.