Abstract
As the scale of electric vehicles grows year by year, disorderly charging of EVs brings great challenges to the safe operation of the power grid and charging management of EV charging service providers. The charging service providers play the role of EV aggregators and aggregate the flexible load of EVs through centralized scheduling strategy. Take profit of EV aggregators and variance of power grid as objectives. Based on the direct scheduling pattern, a multi-objective optimal scheduling model was established and solved by Genetic Algorithm (GA). The results show that under the centralized scheduling strategy of EV aggregators, the difference between peak and valley load of electric power system is reduced, the variance of the grid is lower, the benefits of the aggregator are increased and the EV charging costs are reduced.
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