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电动汽车驱动
★ 5.0
考虑决策依赖不确定性的野火风险下配电网规划
Decision-Dependent Uncertainty-Aware Distribution System Planning Under Wildfire Risk
| 作者 | Felipe Piancó · Alexandre Moreira · Bruno Fanzeres · Ruiwei Jiang · Chaoyue Zhao · Miguel Heleno |
| 期刊 | IEEE Transactions on Power Systems |
| 出版日期 | 2025年5月 |
| 技术分类 | 电动汽车驱动 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | 电力系统 野火 投资规划 决策相关不确定性 配电网优化 |
语言:
中文摘要
电力系统与野火之间的相互作用可能带来严重安全风险与经济损失。在高发野火区域,配电网络在极端天气下可能引发火灾,其运行决策会影响线路故障概率。传统外生型不确定性建模难以刻画此类动态影响,本文提出一种基于决策依赖不确定性(DDU)的配电网投资规划方法,将功率潮流水平和线路加固决策对故障概率的内生性影响纳入分布鲁棒优化框架。模型通过两阶段优化确定最优升级方案(包括新建线路、加固现有线路及部署开关设备),并评估最坏情况下的运行成本。迭代算法用于求解该问题,算例表明所提方法能显著提升电网应对野火风险的韧性。
English Abstract
The interaction between power systems and wildfires can be dangerous and costly. Distribution grids can be liable for the outbreak of wildfires during extreme weather. In wildfire-prone areas, investment planning should consider the impact of operational actions on wildfire-related uncertainties affecting line failure likelihood. In this case, endogenous-based uncertainty modeling should comprise the backbone of the investment planning model viz-a-viz the inability of standard exogenous-based uncertainty modeling. Therefore, we propose a decision-dependent uncertainty (DDU) aware methodology to optimize investment portfolios for distribution systems, considering that high power-flow levels in high-threat areas can ignite wildfires and increase line failure probability. The methodology identifies the best combination of upgrades (new lines, hardening existing lines, and placing switching devices). Methodologically, we propose a two-stage distributionally robust planning optimization problem with DDU that considers the distribution system's multiperiod operation. The first stage determines optimal switching actions and line investments, and the second stage evaluates the worst-case expected operational cost under a DDU framework designed to account for the endogenous impact of power-flow levels and hardening investment decisions in the line failure probabilities. An iterative method is tailored to handle the problem and numerical experiments demonstrate a more prepared grid to deal with wildfire risk.
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SunView 深度解读
该决策依赖不确定性配电网规划技术对阳光电源储能系统及微网解决方案具有重要应用价值。在野火等极端气候高发区域(如美国加州、澳洲),PowerTitan大型储能系统可作为关键韧性资源:通过分布鲁棒优化框架指导储能选址与容量配置,在线路故障时提供孤岛供电支撑;ST系列储能变流器的构网型GFM控制可在主网断电时快速建立微网,保障关键负荷供电。该研究的两阶段优化方法可集成至iSolarCloud平台,结合气象数据与线路状态实时评估故障概率,动态调整储能充放电策略与功率潮流分布,降低设备过载引发火灾风险。对于光储一体化项目,该技术可优化SG逆变器与储能系统的协同控制,提升极端场景下电网韧性与经济性。