Advanced Resilience Planning for Distribution Systems
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866916415739527168 |
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| author | Afzal, Ahmad Bin Mohammed, Nabil Ahmed, Shehab Konstantinou, Charalambos |
| author_facet | Afzal, Ahmad Bin Mohammed, Nabil Ahmed, Shehab Konstantinou, Charalambos |
| contents | Climate change has led to an increase in the frequency and severity of extreme weather events, posing significant challenges for power distribution systems. In response, this work presents a planning approach in order to enhance the resilience of distribution systems against climatic hazards. The framework systematically addresses uncertainties during extreme events, including weather variability and line damage. Key strategies include line hardening, backup diesel generators, and sectionalizers to strengthen resilience. We model spatio-temporal dynamics and costs through a hybrid model integrating stochastic processes with deterministic elements. A two-stage stochastic mixed-integer linear approach is developed to optimize resilience investments against load loss, generator operations, and repairs. Case studies on the IEEE 15-bus benchmark system and a realistic distribution grid model in Riyadh, Saudi Arabia demonstrate enhanced system robustness as well as cost efficiency of 10% and 15%, respectively. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_20219 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Advanced Resilience Planning for Distribution Systems Afzal, Ahmad Bin Mohammed, Nabil Ahmed, Shehab Konstantinou, Charalambos Systems and Control Climate change has led to an increase in the frequency and severity of extreme weather events, posing significant challenges for power distribution systems. In response, this work presents a planning approach in order to enhance the resilience of distribution systems against climatic hazards. The framework systematically addresses uncertainties during extreme events, including weather variability and line damage. Key strategies include line hardening, backup diesel generators, and sectionalizers to strengthen resilience. We model spatio-temporal dynamics and costs through a hybrid model integrating stochastic processes with deterministic elements. A two-stage stochastic mixed-integer linear approach is developed to optimize resilience investments against load loss, generator operations, and repairs. Case studies on the IEEE 15-bus benchmark system and a realistic distribution grid model in Riyadh, Saudi Arabia demonstrate enhanced system robustness as well as cost efficiency of 10% and 15%, respectively. |
| title | Advanced Resilience Planning for Distribution Systems |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2409.20219 |