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• W3210250709 abstract "The increase of extreme weather events with wide-area enduring adverse impact has caused enormous loss to power systems. Coordination of various emergency measures can effectively reduce the overall loss over the time-horizon of these events. However, coordination of preventive dispatch, emergency dispatch, and restorative dispatch in transmission systems under extreme weather conditions has not been thoroughly addressed. To fill this gap, we first propose a methodology to coordinate the above dispatch stages based on a novel hierarchical defender-attacker model (HDAM). In this model, various dispatch stages are modelled as defenders, whereas the extreme weather event is modelled as the attacker. Second, frequency security constraints, load shedding, and transmission line switching are modelled with the piecewise linear AC power flow in the HDAM. Particularly, an adaptive approximation of cosine function in the piecewise linear power flow equation is applied to greatly reduce the computational complexity. Third, the HDAM is recast as a two-stage robust optimization model with binary decision variables in the recourse stage and solved by the nested column-and-constraint generation algorithm. Then, the robust resilience trapezoid and coordinated strategy during extreme weather events are obtained by the proposed methodology. Moreover, by inference-based sensitivity analysis of the discrete line outage scenarios, the critical transmission lines and transformers are identified for pre-event hardening. Comprehensive case studies using IEEE benchmark systems and a Chinese 132-bus system validate that coordination of multiple dispatch stages is effective to enhance power system resilience against extreme weather events by reducing the overall loss." @default.
• W3210250709 created "2021-11-08" @default.
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• W3210250709 date "2022-07-01" @default.
• W3210250709 modified "2023-10-18" @default.
• W3210250709 title "Coordination of Preventive, Emergency and Restorative Dispatch in Extreme Weather Events" @default.
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• W3210250709 doi "https://doi.org/10.1109/tpwrs.2021.3123247" @default.
• W3210250709 hasPublicationYear "2022" @default.
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