Managing Wildfire Risk and Promoting Equity through Optimal Configuration of Networked Microgrids

Publicly accessible License 

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 -
Export Citation to RIS
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

Authors

Sofia Taylor

University of Wisconsin-Madison

Gabriela Setyawan

University of Wisconsin-Madison

Bai Cui

NLR

Ahmed Zamzam

NLR

Line Roald

University of Wisconsin-Madison
Submission Downloads