不断蔓延野火下提升电力系统韧性的序贯运行决策
Sequential Operational Decision-Making for Power System Resilience Under Evolving Wildfires
AI总结：
本文提出一种自动化决策支持框架，将野火蔓延下的电力系统决策建模为随机多阶段规划，结合新算法与随机对偶动态规划方法，在IEEE系统上验证了其提升电网韧性的效果。
AI中文摘要：
本文提出一种新型自动化决策支持框架，旨在通过将野火蔓延过程中的决策制定建模为随机多阶段规划，以提升电力系统韧性及运行韧性。该框架同时考虑预防性与 corrective 行动（注：此处corrective译为 corrective，指纠正性行动），可基于野火蔓延过程中的潜在场景做出自动化自适应决策。此方法考虑野火威胁的动态演化特性，力求在野火全程优化响应策略，目标为最小化野火风险与运行成本，同时降低负荷削减量。该框架计及野火蔓延引发的潜在偶发事件，提出一种基于野火蔓延与系统地理信息构建决策树的新算法，并采用新型随机对偶动态规划方法求解所提优化问题，以获取框架的全局最优解。在不同野火影响场景下的IEEE 30节点系统上验证了所提方法的有效性，随后应用于IEEE 300节点系统以说明其可扩展性。结果表明，所提自动化框架在野火场景下提升电网韧性方面优于单阶段运行优化策略。
英文摘要：
This paper proposes a novel automated decision-support framework aimed at enhancing the resilience of power systems and operational resilience against wildfires by formulating the decision-making process as a stochastic multi-stage programming during a progressive wildfire. The paper develops a framework that takes into account both preventive and corrective actions, enabling automated and adaptive decisions based on potential scenarios over the course of a wildfire's progression. This approach considers the evolving nature of the wildfire threat and seeks to optimize the response strategies accordingly throughout its duration. The objective is to minimize wildfire risk and operational costs while reducing load curtailment. The framework accounts for potential contingencies caused by progressive wildfires. A novel algorithm is proposed to construct a decision tree based on wildfire progression and system geographical information. Additionally, a novel stochastic dual dynamic programming approach is deployed to solve the proposed optimization problem, achieving a global optimum for the framework. The effectiveness of the proposed method is demonstrated on the IEEE 30-bus system under various wildfire impact scenarios and is then applied to the IEEE 300-bus system to illustrate the scalability of the proposed approach. The results highlight the advantages of the proposed automated framework over a single-stage operational optimization strategy in enhancing power grid resilience under wildfire conditions.
