Abstract
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.
Highlights
The power system is the most complicated man-made system in the world, so failures and blackouts are inevitable
How to improve the ability of the power system to deal with blackouts, how to quickly restore critical loads and extend the power supply time of critical loads as much as possible, which could improve the resilience of the power system [4] and minimize the losses caused by the blackout, is a problem that many researchers are eager to solve
(3) The proposed strategy is compared with the strategy that does not allocate electric vehicles (EVs) to the charging stations reasonably, and the strategy that neither allocates EVs reasonably nor considers multi-period coordinated load restoration, respectively, to verify the effectiveness and superiority of the strategy proposed in this paper
Summary
The power system is the most complicated man-made system in the world, so failures and blackouts are inevitable. Paper [25] proposed the idea of selecting the optimal route based on the constructed transportation network model and the Dijkstra algorithm, but did not mention the specific process It only directly mentioned the EV charging and discharging capacity time-sequence diagram. J. 2021, 12, 121 buses, and proposed a method for selecting the location of charging stations considering the transportation network It did not take into account the specific dispatching problems during a blackout which is the focus point of this article. In the first stage of the strategy, the objective is to maximize the weighted power supply time of load, making charging station assignment decisions for EVs that are willing to participate in load restoration services, and determining the output of distributed generators and charging stations in each period. Considering the traffic congestion of each road section, the specific optimal travelling route for each EV is recommended. (2) The model is processed by multiple linearization, second-order conic relaxation (SOCR) and the Dijkstra algorithm to ensure the solvability and accuracy of the model. (3) The proposed strategy is compared with the strategy that does not allocate EVs to the charging stations reasonably, and the strategy that neither allocates EVs reasonably nor considers multi-period coordinated load restoration, respectively, to verify the effectiveness and superiority of the strategy proposed in this paper
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