AUTHOR=Wang Xueyan , Zhang Bingye , Li Dengdiao , Sun Jinzhou , Wang Yu , Wang Xinyu , Liang Qu , Tang Fei 

TITLE=Research on data-driven, multi-component distribution network attack planning methods

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 12 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2024.1425197

DOI=10.3389/fenrg.2024.1425197

ISSN=2296-598X

ABSTRACT=As the power information physical system undergoes continual advancement, mobile energy storage has become a pivotal component in the planning and orchestration of multi-component distribution networks. Furthermore, the evolution and enhancement of big data technologies have significantly contributed to enhancing the rationality and efficacy of various distribution network planning and layouts. Nevertheless, the multi-distribution network has also confronted numerous network attacks, with a progressively rising probability and severity.In this study, Petri net is initially employed as a modeling technique to delineate the network attack flow within the distribution network.Subsequently, the data from prior network attacks are consolidated and scrutinized to evaluate the vulnerability of the CPS system, thereby identifying the most critical network attack pattern for the multi-component distribution network. Following this, the DAD planning methodology is applied for scale modeling, incorporating the rapidly evolving mobile energy storage into the pre-layout, aiming to mitigate the detrimental impact of network attacks on the power grid.Ultimately, the C&CG algorithm is utilized to simulate and validate the proposed planning strategy in a 33-node system, with multiple control groups established to demonstrate the viability and merits of the proposed strategy.