How Network Topology Affects the Strength of Dangerous Power Grid Perturbations
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arXiv
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866912549893570560 |
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| author | Alvares, Calvin Banerjee, Soumitro |
| author_facet | Alvares, Calvin Banerjee, Soumitro |
| contents | Reasonably large perturbations may push a power grid from its stable synchronous state into an undesirable state. Identifying vulnerabilities in power grids by studying power grid stability against such perturbations can aid in preventing future blackouts. Probabilistic stability quantifiers such as basin stability, which measures the asymptotic stability of a system, and survivability, which measures the transient stability of a system, have been commonly used to quantify the stability of nodes in a power grid. However, these quantifiers do not provide information about the strength of perturbations that destabilize the system. To measure the strength of perturbations beyond which the stability of the system gets compromised, we employ two probabilistic distance-based stability measures -- basin stability bound, which deals with a system's asymptotic behaviour, and survivability bound, a newly defined stability measure that deals with a system's transient behaviour. Using these stability quantifiers, we conduct a detailed study on the impact of network topology on the strength of dangerous power grid perturbations. In this, we uncover a new class of highly vulnerable nodes that were previously unknown. Additionally, we establish connections with tree-like network structures and node connectivity to lowly stable nodes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_00552 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | How Network Topology Affects the Strength of Dangerous Power Grid Perturbations Alvares, Calvin Banerjee, Soumitro Adaptation and Self-Organizing Systems Reasonably large perturbations may push a power grid from its stable synchronous state into an undesirable state. Identifying vulnerabilities in power grids by studying power grid stability against such perturbations can aid in preventing future blackouts. Probabilistic stability quantifiers such as basin stability, which measures the asymptotic stability of a system, and survivability, which measures the transient stability of a system, have been commonly used to quantify the stability of nodes in a power grid. However, these quantifiers do not provide information about the strength of perturbations that destabilize the system. To measure the strength of perturbations beyond which the stability of the system gets compromised, we employ two probabilistic distance-based stability measures -- basin stability bound, which deals with a system's asymptotic behaviour, and survivability bound, a newly defined stability measure that deals with a system's transient behaviour. Using these stability quantifiers, we conduct a detailed study on the impact of network topology on the strength of dangerous power grid perturbations. In this, we uncover a new class of highly vulnerable nodes that were previously unknown. Additionally, we establish connections with tree-like network structures and node connectivity to lowly stable nodes. |
| title | How Network Topology Affects the Strength of Dangerous Power Grid Perturbations |
| topic | Adaptation and Self-Organizing Systems |
| url | https://arxiv.org/abs/2401.00552 |