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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2401.17994 |
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| _version_ | 1866916111292825600 |
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| author | Salman, Umar T. Wang, Zongjie Hansen, Timothy M. |
| author_facet | Salman, Umar T. Wang, Zongjie Hansen, Timothy M. |
| contents | This paper addresses the challenges of high-impact low-probability (HILP) events by proposing a novel capacity reserve event market for mobile generation assets, aimed at supporting the transmission network during such incidents. Despite the usefulness of portable generators and mobile energy units in restoring power, there are drawbacks such as environmental impact, finite operation, and complex cost recovery. The proposed market integrates these resources into a dispatch framework based on pre-established contracts, ensuring fair compensation and considering factors like capacity, pricing, and travel distance. Resource owners receive advanced notifications for potential events, allowing them to adjust their bids for cost recovery. Simulations on an IEEE 30-bus case have been conducted to demonstrate the model effectiveness in increasing grid resiliency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_17994 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Optimizing Grid Resilience: A Capacity Reserve Market for High Impact Low Probability Events Salman, Umar T. Wang, Zongjie Hansen, Timothy M. Systems and Control This paper addresses the challenges of high-impact low-probability (HILP) events by proposing a novel capacity reserve event market for mobile generation assets, aimed at supporting the transmission network during such incidents. Despite the usefulness of portable generators and mobile energy units in restoring power, there are drawbacks such as environmental impact, finite operation, and complex cost recovery. The proposed market integrates these resources into a dispatch framework based on pre-established contracts, ensuring fair compensation and considering factors like capacity, pricing, and travel distance. Resource owners receive advanced notifications for potential events, allowing them to adjust their bids for cost recovery. Simulations on an IEEE 30-bus case have been conducted to demonstrate the model effectiveness in increasing grid resiliency. |
| title | Optimizing Grid Resilience: A Capacity Reserve Market for High Impact Low Probability Events |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2401.17994 |