论文标题

考虑放置和操作时间表的风险降低的动态热等级的两阶段次管次量级优化

Two-Stage Submodular Optimization of Dynamic Thermal Rating for Risk Mitigation Considering Placement and Operation Schedule

论文作者

Long, Qinfei, Liu, Junhong, Ren, Chenhao, Yin, Wenqian, Liu, Feng, Hou, Yunhe

论文摘要

级联失败会给目前的社会带来重大风险。为了有效缓解风险,可以将动态热等级(DTR)技术作为一种具有成本效益的策略来利用潜在的传输能力。从服务寿命和胸罩悖论的角度来看,共同优化更改系统状态的DTR放置和操作计划是一个重要且挑战,这是一个仅具有离散变量的两阶段组合问题,仅基于传统模型而没有近似保证和维度诅咒。因此,目前的工作提出了DTR的新型两阶段的下二次优化(TSSO),以考虑放置和操作时间表,以减轻风险。具体而言,它在第一阶段优化了具有适当冗余的DTR放置,然后确定第二阶段每个系统状态的相应DTR操作。在马尔可夫的条件下,在降低风险的子功能中,可以首次证明TSSO的总目标功能的次函数。基于此,通过协调单独的曲率和误差形式,开发了一种最先进的有效解决算法,该算法可以比以前的研究提供更好的近似保证。通过病例结果验证了所提出的算法的性能。

Cascading failure causes a major risk to society currently. To effectively mitigate the risk, dynamic thermal rating (DTR) technique can be applied as a cost-effective strategy to exploit potential transmission capability. From the perspectives of service life and Braess paradox, it is important and challenging to jointly optimize the DTR placement and operation schedule for changing system state, which is a two-stage combinatorial problem with only discrete variables, suffering from no approximation guarantee and dimension curse only based on traditional models. Thus, the present work proposes a novel two-stage submodular optimization (TSSO) of DTR for risk mitigation considering placement and operation schedule. Specifically, it optimizes DTR placement with proper redundancy in first stage, and then determines the corresponding DTR operation for each system state in second stage. Under the condition of the Markov and submodular features in sub-function of risk mitigation, the submodularity of total objective function of TSSO can be proven for the first time. Based on this, a state-of-the-art efficient solving algorithm is developed that can provide a better approximation guarantee than previous studies by coordinating the separate curvature and error form. The performance of the proposed algorithms is verified by case results.

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