Risk prediction based preventive typhoon defending for semi-independent power system

Shankang Cao, Fanrong Wei, Xiangning Lin, Xitao Yuan, Qiyuan Huang and Hong Xiang

Applied Energy, 2025, vol. 377, issue PC, No S0306261924017720

Abstract: The regional power grid that relies on the coordinated operation of internal generators and feed-in power through transmission lines (TLs), referred to as a semi-independent power grid (SIPG), enjoys potential self-sustaining ability under TL outage events induced by typhoon disasters by self-regulating. However, due to the instantaneous power failure of TLs resulting from physical damage, which is far shorter than the adjustment time of internal generators, SIPG will presumably collapse facing sudden massive power shortage without a previous resource scheduling policy. To ensure the safe operation of SIPG under typhoon disasters, a preventive typhoon-defending scheme is proposed. First, derived from the idea of Few-Shot Class-Incremental Learning (FSCIL), a risk prediction model is constructed to fairly assess the outage probability of TLs in the absence of tower damage samples. Noteworthily, real features of towers are extracted. Thus, convincing decision-making is provided for the preventive scheduling strategy. Subsequently, a multistage stochastic optimizing strategy considering the outage probability of TLs is proposed. Specifically, generators and loads in SIPG are pre-scheduled to reduce the interactive power demand from the main grid, alleviating the instantaneous power shortage caused by potential TL outage events. The modified IEEE 24-reliability test system is used to validate the proposed scheme.

Keywords: Few-shot class-incremental learning; Risk prediction; Proactive scheduling; Semi-independent power grid (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2024.124389

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