Sharing the Load: Considering Fairness in De-energization Scheduling to Mitigate Wildfire Ignition Risk using Rolling Optimization
Wildfires are a threat to public safety and have increased in both frequency and severity due to climate change. To mitigate wildfire ignition risks, electric power system operators proactively de-energize high-risk power lines during "public safety power shut-off" (PSPS) events. Line de-energizations can cause communities to lose power, which may result in negative economic, health, and safety impacts. Furthermore, the same communities may repeatedly experience power shutoffs over the course of a wildfire season, which compounds these negative impacts. However, there may be many combinations of power lines whose de-energization will result in about the same reduction of system-wide wildfire risk, but the associated power outages affect different communities. Therefore, one may raise concerns regarding the fairness of de-energization decisions. Accordingly, this paper proposes a framework to select lines to de-energize in order to balance wildfire risk reduction, total load shedding, and fairness considerations. The goal of the framework is to prevent a small fraction of communities from disproportionally being impacted by PSPS events, and to instead more equally share the burden of power outages. For a geolocated test case in the southwestern United States, we use actual California demand data as well as real wildfire risk forecasts to simulate PSPS events during the 2021 wildfire season and compare the performance of various methods for promoting fairness. Our results demonstrate that the proposed formulation can provide significantly more fair outcomes with limited impacts on system-wide performance.
Code (0)
등록된 구현이 없습니다.
Tasks
FairnessSchedulingSimilar Papers 제목 키워드 기반
Locality-aware Fair Scheduling in LLM Serving
Large language model (LLM) inference workload dominates a wide variety of modern AI applications, ranging from multi-turn conversation to document analysis. Balancing fairness and efficiency is critical for managing dive…
FairnessLanguage ModelingLanguage ModellingLarge Language Model+1A Profit Sharing Mechanism for Coordinated Power Traffic System
During the scheduling process, the traffic network operator (TNO) and the distribution network operator (DNO) act noncooperatively. Under the TNO management, the distribution of charging loads may exacerbate the local su…
SchedulingOptimizing Transmission Infrastructure Investments to Support Line De-energization for Mitigating Wildfire Ignition Risk
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, …
ManagementMulti-objective Optimization of Clustering-based Scheduling for Multi-workflow On Clouds Considering Fairness
Distributed computing, such as cloud computing, provides promising platforms to execute multiple workflows. Workflow scheduling plays an important role in multi-workflow execution with multi-objective requirements. Altho…
Cloud ComputingClusteringDistributed ComputingFairness+1The Dilemma of Electricity Grid Expansion Planning in Areas at the Risk of Wildfire
The utilities consider public safety power shut-offs imperative for the mitigation of wildfire risk. This paper presents expansion planning of power system under fire hazard weather conditions. The power lines are quanti…