Balancing Wildfire Risk and Power Outages Through Optimized Power Shut-Offs

Rhodes, Noah; Ntaimo, Lewis; Roald, Line

doi:10.1109/tpwrs.2020.3046796

Cited by 62 publications

(69 citation statements)

References 16 publications

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“…Seasonal wildfires are an excellent example of when the deployment of particle filter systems can provide large reductions in indoor PM2.5 concentration and improve health outcomes [29,109,110]. During wildfires, it is also quite common for power outages to occur [111] and thus particle filter systems may be powered by a battery with a finite storage capacity. Under these conditions, there is a benefit to significantly reducing the runtime.…”

Section: Exposure Reductionmentioning

confidence: 99%

Particulate matter concentrations in social housing

Mendell

Mahdavi

Siegel

2022

Sustainable Cities and Society

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Section: Exposure Reductionmentioning

confidence: 99%

Particulate matter concentrations in social housing

Mendell

Mahdavi

Siegel

2022

Sustainable Cities and Society

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“…In [14], the authors developed a power system planning strategy to reflect the impact of electric vehicle evacuations on power system resiliency during wildfire events. In [15], the authors modeled wildfire risks in power systems and developed an optimal power shut-off strategy using optimal power flow.…”

Section: High Risk Powerlinementioning

confidence: 99%

Data-Driven Power System Optimal Decision Making Strategy under Wildfire Events

Hong¹,

Wang²,

Yao³

et al. 2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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Wildfire activities are increasing in the western United States in recent years, causing escalating threats to power systems. This paper developed an optimal and data-driven decision-making framework that improves power system resilience under wildfire risks. An optimal load shedding plan is formulated based on optimal power flow analysis. To avoid power system cascading failure caused by wildfire, we added additional transmission line flow constraints based on the identification of power lines with high ignition risk. Finally, a data-driven method is developed, leveraging multiple machine learning techniques, to model the complex correlations between input wildfire scenarios and the output power management strategy with significantly reduced computational complexities. The proposed data-driven decision-making framework can reduce the safety impacts on the electricity consumers, improve power system resilience under wildfire events.

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“…Using this method and taking into account the risk of a wildfire caused by electric components and the short-term mitigation of wildfire risks, an optimization model was created to minimize a wildfire risk occurring due to electric power system components. At the same time, preserving electricity supplies to as many customers as possible is at the highest level [56].…”

Section: Different Hazard Assessment or Prevention Examplesmentioning

confidence: 99%

Early Warning Weather Hazard System for Power System Control

2022

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Power systems and their primary components, mostly the transmission and distribution of overhead lines, substations, and other power facilities, are distributed in space and are exposed to various atmospheric and meteorological conditions. These conditions carry a certain level of risk for reliable electrical power delivery. Various atmospheric hazards endanger the operation of power systems, where the most significant are thunderstorms, wildfire events, and floods which can cause various ranges of disturbances, faults, and damages to the power grid, or even negatively affect the quality of life. By utilizing a weather monitoring and early warning system, it is possible to ensure a faster reaction against different weather-caused fault detections and elimination, to ensure a faster and more adequate preparation for fighting extreme weather events, while maintaining overhead line protection and fault elimination. Moreso, it is possible to bypass overhead lines that have the highest risk of unfavorable meteorological events and hazards, and reroute the energy, thus providing electricity to endangered areas in times of need while minimizing blackouts, and consequently, improving the quality of human life. This paper will present an analysis of the various risks of atmospheric phenomena, in the meteorological and climate context, and discuss various power system components, the power system control, operations, planning, and power quality. A concept with the main functionalities and data sources needed for the establishment of an early warning weather hazard system will be proposed. The proposed solution can be used as a utility function in power system control to mitigate risks to the power system due to atmospheric influences and ongoing climate change.

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Balancing Wildfire Risk and Power Outages Through Optimized Power Shut-Offs

Cited by 62 publications

References 16 publications

Particulate matter concentrations in social housing

Particulate matter concentrations in social housing

Data-Driven Power System Optimal Decision Making Strategy under Wildfire Events

Early Warning Weather Hazard System for Power System Control

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