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To cope with the frequent blackouts in recent years and improve the resilience of the distribution network, a two-stage multi-period coordinated load restoration strategy for the distribution network based on intelligent route recommendation of electric vehicles (EVs) is proposed. The first stage of the model aims at maximizing the weighted power supply time of load, minimizing the total network loss, optimizing the output of each power supply source at each time period, and determining the optimal charging station assignment scheme for schedulable EVs. The second stage is based on the optimal charging station assignment scheme for EV determined in the first stage, with the shortest total time for all EVs to reach the designated charging stations as the objective and determining the optimal travel route of each EV. The model dispatches the idle EVs during blackout as a flexible power supply resource, realizing the multi-period coordination output of multiple sources and recommending the routes for EVs to reach the designated charging stations to optimize the restoration effect of critical loads. The methods of piecewise linearization, second-order conic relaxation (SOCR) and the Dijkstra algorithm are applied to ensure the feasibility and accuracy of the model. Finally, by comparing the proposed strategy with two different single-stage strategies, the effect of these three strategies on the critical load’s restoration and the operation status of the distribution network is further analyzed, which verifies the effectiveness and superiority of the proposed strategy.

Two-Stage Multi-Period Coordinated Load Restoration Strategy for Distribution Network Based on Intelligent Route Recommendation of Electric Vehicles