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Resilience assessment of mobile emergency generator-assisted distribution networks: A stochastic geometry approach

Year: 2023
Type: article
Abstract: The escalation of extreme weather events threatens power system infrastructures significantly. Mobile emergency generators (MEGs) render flexible restoration strategies against destructive events. However, with the continuous expansion of distribution networks, quantifying the impacts of MEGs becomes increasingly challenging due to extreme weather event-induced uncertainties. In this paper, we propose a stochastic geometry-based method for assessing the impact of MEG deployment on distribution networks under extreme weather events by investigating structural features. Firstly, we propose a distance measure to depict the electrical connection between power grid components. Subsequently, we adopt the point process and Voronoi tessellation to describe the spatial distribution of power grid components and the service coverage provided by MEGs in different scenarios. Then, we propose a set of assessment metrics to evaluate the survivability of power grid components and the resilience of distribution networks under extreme weather events. Finally, we derive accurate analytical expressions for the distance distribution and resilience metrics, such as coverage probability and load shedding, enabling us to explore the relationship between MEG deployment decisions, structure features, and power grid resilience. The proposed method empowers us to analytically assess the impact of MEG deployment on the resilience of distribution networks and provides beneficial insights to formulate efficient measures for enhancing resilience. Case studies demonstrate that the proposed method is accurate and efficient in dealing with network analysis and assessment problems for distribution networks under massive scenarios.
DOI: 10.1016/j.ject.2023.10.002
Language: English
Open Access status: diamond
OpenAlex ID: W4387745839
FWCI: 0.356
Cites: 40
Cited by: 5
Related to: 10