论文标题

优化传输基础设施投资,以支持线路化的线路化,以减轻野火点火风险

Optimizing Transmission Infrastructure Investments to Support Line De-energization for Mitigating Wildfire Ignition Risk

论文作者

Kody, Alyssa, Piansky, Ryan, Molzahn, Daniel K.

论文摘要

在美国西部等地区,野火对公共安全构成了日益增长的风险,并且从历史上看,电力系统已经点燃了一些最具破坏性的野火。为了降低野火点火风险,作为“公共安全功率关闭”(PSP)事件的一部分,电力系统运营商在极端野火条件下先发出高风险电力线。尽管能够大大降低急性野火风险,但PSP事件也可能导致大量的负载降低,因为部分脱发的系统可能无法满足所有客户需求。在这项工作中,我们调查了基础设施投资可以在多大程度上通过减少负载和野火点火风险来支持PSP事件期间的系统操作。我们考虑安装网格尺度电池,太阳能光伏以及线路硬化或维护措施(例如,地下或增加植被管理)。最佳选择这些基础架构投资的位置,类型和大小需要考虑与PSP事件相关的线路启用的线路。因此,本文提出了一种多周期优化公式,该公式可以定位和规模基础设施投资,同时选择线路脱水,以最大程度地减少野火点火风险和负载降低。使用两个地理测试案例以及现实的基础设施投资参数以及美国地质调查局的实际野火风险数据来评估该公式。我们通过模拟整个2021年野火季节的脱振决策来评估投资选择的性能,并使用优化的基础设施位置。由于不同的测试案例,预算和运营商的优先事项的投资决策差异很大,数值结果证明了拟议的配方在为不同环境定制投资选择时的价值。

Wildfires pose a growing risk to public safety in regions like the western United States, and, historically, electric power systems have ignited some of the most destructive wildfires. To reduce wildfire ignition risks, power system operators preemptively de-energize high-risk power lines during extreme wildfire conditions as part of "Public Safety Power Shutoff" (PSPS) events. While capable of substantially reducing acute wildfire risks, PSPS events can also result in significant amounts of load shedding as the partially de-energized system may not be able to supply all customer demands. In this work, we investigate the extent to which infrastructure investments can support system operations during PSPS events by enabling reduced load shedding and wildfire ignition risk. We consider the installation of grid-scale batteries, solar PV, and line hardening or maintenance measures (e.g., undergrounding or increased vegetation management). Optimally selecting the locations, types, and sizes of these infrastructure investments requires considering the line de-energizations associated with PSPS events. Accordingly, this paper proposes a multi-period optimization formulation that locates and sizes infrastructure investments while simultaneously choosing line de-energizations to minimize wildfire ignition risk and load shedding. This formulation is evaluated using two geolocated test cases along with realistic infrastructure investment parameters and actual wildfire risk data from the US Geological Survey. We evaluate the performance of investment choices by simulating de-energization decisions for the entire 2021 wildfire season with optimized infrastructure placements. With investment decisions varying significantly for different test cases, budgets, and operator priorities, the numerical results demonstrate the proposed formulation's value in tailoring investment choices to different settings.

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