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Wildfire Modeling: Designing a Market to Restore Assets

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  • Ramandeep Kaur Bagri
  • Yihsu Chen

Abstract

In the past decade, summer wildfires have become the norm in California, and the United States of America. These wildfires are caused due to variety of reasons. The state collects wildfire funds to help the impacted customers. However, the funds are eligible only under certain conditions and are collected uniformly throughout California. Therefore, the overall idea of this project is to look for quantitative results on how electrical corporations cause wildfires and how they can help to collect the wildfire funds or charge fairly to the customers to maximize the social impact. The research project aims to propose the implication of wildfire risk associated with vegetation, and due to power lines and incorporate that in dollars. Therefore, the project helps to solve the problem of collecting wildfire funds associated with each location and incorporate energy prices to charge their customers according to their wildfire risk related to the location to maximize the social surplus for the society. The thesis findings will help to calculate the risk premium involving wildfire risk associated with the location and incorporate the risk into pricing. The research of this submitted proposal provides the potential contribution towards detecting the utilities associated wildfire risk in the power lines, which can prevent wildfires by controlling the line flows of the system. Ultimately, the goal of this proposal is a social benefit to save money for the electrical corporations and their customers in California, who pay flat charges for Wildfire Fund each month $0.00580/kWh (in dollars). Therefore, this proposal will propose new method to collect wildfire fund with maximum customer surplus for future generations.

Suggested Citation

  • Ramandeep Kaur Bagri & Yihsu Chen, 2022. "Wildfire Modeling: Designing a Market to Restore Assets," Papers 2205.13773, arXiv.org, revised Mar 2024.
    • Handle: RePEc:arx:papers:2205.13773
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    References listed on IDEAS

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    1. Yihsu Chen & Benjamin Hobbs & Sven Leyffer & Todd Munson, 2006. "Leader-Follower Equilibria for Electric Power and NO x Allowances Markets," Computational Management Science, Springer, vol. 3(4), pages 307-330, September.
    2. Lisa Zaval & Elizabeth A. Keenan & Eric J. Johnson & Elke U. Weber, 2014. "How warm days increase belief in global warming," Nature Climate Change, Nature, vol. 4(2), pages 143-147, February.
    3. Judah Cohen & Karl Pfeiffer & Jennifer A. Francis, 2018. "Warm Arctic episodes linked with increased frequency of extreme winter weather in the United States," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
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