Wildfire Modeling: Designing a Market to Restore Assets

Fuente: arXiv
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Auteurs principaux: Bagri, Ramandeep Kaur, Chen, Yihsu
Format: Preprint
Publié: 2022
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author Bagri, Ramandeep Kaur
Chen, Yihsu
author_facet Bagri, Ramandeep Kaur
Chen, Yihsu
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2205_13773
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Wildfire Modeling: Designing a Market to Restore Assets
Bagri, Ramandeep Kaur
Chen, Yihsu
General Economics
Economics
14J26 (Secondary)
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.
title Wildfire Modeling: Designing a Market to Restore Assets
topic General Economics
Economics
14J26 (Secondary)
url https://arxiv.org/abs/2205.13773