Mitigating the Impact of Uncertain Wildfire Risk on Power Grids through Topology Control
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866929451832442880 |
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| author | Zhou, Yuqi Sundar, Kaarthik Deka, Deepjyoti Zhu, Hao |
| author_facet | Zhou, Yuqi Sundar, Kaarthik Deka, Deepjyoti Zhu, Hao |
| contents | Wildfires pose a significant threat to the safe and reliable operations of the electric grid. To mitigate wildfire risk, system operators resort to public safety power shutoffs, or PSPS, that shed load for a subset of customers. As wildfire risk forecasts are stochastic, such decision-making may often be sub-optimal. This paper proposes a two-stage topology control problem that jointly minimizes generation and load-shedding costs in the face of uncertain fire risk. Compared to existing work, we include preand post-event topology control actions and consider scenarios where the wildfire risk is known with low and high confidence. The effectiveness of the proposed approach is demonstrated using a benchmark test system, artificially geo-located in Southern California, and using stochastic wildfire risk data that exists in the literature. Our work provides a crucial study of the comparative benefits of pre-event versus post-event control and the effects of wildfire risk accuracy on each control strategy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2303_07558 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Mitigating the Impact of Uncertain Wildfire Risk on Power Grids through Topology Control Zhou, Yuqi Sundar, Kaarthik Deka, Deepjyoti Zhu, Hao Systems and Control Optimization and Control Wildfires pose a significant threat to the safe and reliable operations of the electric grid. To mitigate wildfire risk, system operators resort to public safety power shutoffs, or PSPS, that shed load for a subset of customers. As wildfire risk forecasts are stochastic, such decision-making may often be sub-optimal. This paper proposes a two-stage topology control problem that jointly minimizes generation and load-shedding costs in the face of uncertain fire risk. Compared to existing work, we include preand post-event topology control actions and consider scenarios where the wildfire risk is known with low and high confidence. The effectiveness of the proposed approach is demonstrated using a benchmark test system, artificially geo-located in Southern California, and using stochastic wildfire risk data that exists in the literature. Our work provides a crucial study of the comparative benefits of pre-event versus post-event control and the effects of wildfire risk accuracy on each control strategy. |
| title | Mitigating the Impact of Uncertain Wildfire Risk on Power Grids through Topology Control |
| topic | Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2303.07558 |