Managing Wildfire Risk and Promoting Equity through Optimal Configuration of Networked Microgrids
As climate change increases the risk of large-scale wildfires, wildfire ignitions from electric power lines are a growing concern. To mitigate the wildfire ignition risk, many electric utilities de-energize power lines to prevent electric faults and failures. These preemptive power shutoffs are effective in reducing ignitions, but they could result in wide-scale power outages. Advanced technology, such as networked microgrids, can help reduce the size of the resulting power outages; however, even microgrid technology might not be sufficient to supply power to everyone, thus forcing hard questions about how to prioritize the provision of power among customers. In this paper, we present an optimization problem that configures networked microgrids to manage wildfire risk while maximizing the power served to customers; however, rather than simply maximizing the amount of power served in kilowatts, our formulation also considers the ability of customers to cope with power outages, as measured by social vulnerability, and it discourages the disconnection of particularly vulnerable customer groups. To test our model, we leverage a synthetic but realistic distribution feeder, along with publicly available social vulnerability indices and satellite-based wildfire risk map data, to quantify the parameters in our optimal decision-making model. Our case study results demonstrate the benefits of networked microgrids in limiting load shed and promoting equity during scenarios with high wildfire risk.
Citation Formats
TY - DATA
AB - As climate change increases the risk of large-scale wildfires, wildfire ignitions from electric power lines are a growing concern. To mitigate the wildfire ignition risk, many electric utilities de-energize power lines to prevent electric faults and failures. These preemptive power shutoffs are effective in reducing ignitions, but they could result in wide-scale power outages. Advanced technology, such as networked microgrids, can help reduce the size of the resulting power outages; however, even microgrid technology might not be sufficient to supply power to everyone, thus forcing hard questions about how to prioritize the provision of power among customers. In this paper, we present an optimization problem that configures networked microgrids to manage wildfire risk while maximizing the power served to customers; however, rather than simply maximizing the amount of power served in kilowatts, our formulation also considers the ability of customers to cope with power outages, as measured by social vulnerability, and it discourages the disconnection of particularly vulnerable customer groups. To test our model, we leverage a synthetic but realistic distribution feeder, along with publicly available social vulnerability indices and satellite-based wildfire risk map data, to quantify the parameters in our optimal decision-making model. Our case study results demonstrate the benefits of networked microgrids in limiting load shed and promoting equity during scenarios with high wildfire risk.
AU - Taylor, Sofia
A2 - Setyawan, Gabriela
A3 - Cui, Bai
A4 - Zamzam, Ahmed
A5 - Roald, Line
DB - C-MIX - Community Microgrid Information Exchange
DP - Open EI | National Laboratory of the Rockies
DO - 10.1145/3575813.3595196
KW - Battery energy storage
KW - Solar
KW - Photovoltaics
KW - PV
KW - Diesel generators
KW - Other liquid-fuel generators
KW - Wind energy
KW - Resilience
KW - Extreme weather
KW - Case studies
KW - Performance
KW - Community engagement
KW - Tribal engagement
KW - Stakeholder engagement
LA - English
DA - 2023/06/01
PY - 2023
PB - University of Wisconsin-Madison
T1 - Managing Wildfire Risk and Promoting Equity through Optimal Configuration of Networked Microgrids
UR - https://doi.org/10.1145/3575813.3595196
ER -
Taylor, Sofia, et al. Managing Wildfire Risk and Promoting Equity through Optimal Configuration of Networked Microgrids. University of Wisconsin-Madison, 1 June, 2023, C-MIX - Community Microgrid Information Exchange. https://doi.org/10.1145/3575813.3595196.
Taylor, S., Setyawan, G., Cui, B., Zamzam, A., & Roald, L. (2023). Managing Wildfire Risk and Promoting Equity through Optimal Configuration of Networked Microgrids. [Data set]. C-MIX - Community Microgrid Information Exchange. University of Wisconsin-Madison. https://doi.org/10.1145/3575813.3595196
Taylor, Sofia, Gabriela Setyawan, Bai Cui, Ahmed Zamzam, and Line Roald. Managing Wildfire Risk and Promoting Equity through Optimal Configuration of Networked Microgrids. University of Wisconsin-Madison, June, 1, 2023. Distributed by C-MIX - Community Microgrid Information Exchange. https://doi.org/10.1145/3575813.3595196
@misc{CMIX_Dataset_114,
title = {Managing Wildfire Risk and Promoting Equity through Optimal Configuration of Networked Microgrids},
author = {Taylor, Sofia and Setyawan, Gabriela and Cui, Bai and Zamzam, Ahmed and Roald, Line},
abstractNote = {As climate change increases the risk of large-scale wildfires, wildfire ignitions from electric power lines are a growing concern. To mitigate the wildfire ignition risk, many electric utilities de-energize power lines to prevent electric faults and failures. These preemptive power shutoffs are effective in reducing ignitions, but they could result in wide-scale power outages. Advanced technology, such as networked microgrids, can help reduce the size of the resulting power outages; however, even microgrid technology might not be sufficient to supply power to everyone, thus forcing hard questions about how to prioritize the provision of power among customers. In this paper, we present an optimization problem that configures networked microgrids to manage wildfire risk while maximizing the power served to customers; however, rather than simply maximizing the amount of power served in kilowatts, our formulation also considers the ability of customers to cope with power outages, as measured by social vulnerability, and it discourages the disconnection of particularly vulnerable customer groups. To test our model, we leverage a synthetic but realistic distribution feeder, along with publicly available social vulnerability indices and satellite-based wildfire risk map data, to quantify the parameters in our optimal decision-making model. Our case study results demonstrate the benefits of networked microgrids in limiting load shed and promoting equity during scenarios with high wildfire risk.},
url = {https://cmix.openei.org/submissions/114},
year = {2023},
howpublished = {C-MIX - Community Microgrid Information Exchange, University of Wisconsin-Madison, https://doi.org/10.1145/3575813.3595196},
note = {Accessed: 2026-08-06},
doi = {10.1145/3575813.3595196}
}
https://dx.doi.org/10.1145/3575813.3595196
Details
Data from Jun 1, 2023
Last updated Mar 30, 2026
Submitted Jun 2, 2026
Organization
University of Wisconsin-Madison
Contact
Sofia Taylor

