Considering that the charging behaviors of users of electric vehicles (EVs) (including charging time and charging location) are random and uncertain and that the disorderly charging of EVs brings new challenges to the power grid, this paper proposes an optimal electricity pricing strategy for EVs based on region division and time division. Firstly, by comparing the number of EVs and charging stations in different districts of a city, the demand ratio of charging stations per unit is calculated. Secondly, according to the demand price function and the principle of profit maximization, the charging price between different districts of a city is optimized to guide users to charge in districts with more abundant charging stations. Then, based on the results of the zonal pricing strategy, the time-of-use (TOU) pricing strategy in different districts is discussed. In the TOU pricing model, consumer satisfaction, the profit of power grid enterprises, and the load variance of the power grid are considered comprehensively. Taking the optimization of the comprehensive index as the objective function, the TOU pricing optimization model of EVs is constructed. Finally, the nondominated sorting genetic algorithm (NSGA-II) is introduced to solve the above optimization problems. The specific data of EVs in a municipality directly under the Central Government are taken as examples for this analysis. The empirical results demonstrate that the peak-to-valley ratio of a certain day in the city is reduced from 56.8% to 43% by using the optimal pricing strategy, which further smooth the load curve and alleviates the impact of load fluctuation. To a certain extent, the problem caused by the uneven distribution of electric vehicles and charging stations has been optimized. An orderly and reasonable electricity pricing strategy can guide users to adjust charging habits, to ensure grid security, and to ensure the economic benefits of all parties.

中文翻译：

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基于时空维度的电动汽车充电站绿色行为最优定价策略

考虑到电动汽车用户的充电行为（包括充电时间和充电位置）是随机且不确定的，并且电动汽车的无序充电给电网带来了新的挑战，本文提出了电动汽车的最优电价策略基于区域划分和时间划分。首先，通过比较城市不同地区的电动汽车和充电站的数量，计算出每单位充电站的需求率。其次，根据需求价格函数和利润最大化的原则，对城市不同地区之间的收费价格进行优化，以指导用户在充电站数量较多的地区进行收费。然后，根据区域定价策略的结果，讨论了不同地区的使用时间（TOU）定价策略。在TOU定价模型中，综合考虑了消费者满意度，电网企业的利润以及电网的负荷变化。以综合指标的优化为目标函数，构建电动汽车的分时定价优化模型。最后，引入非支配排序遗传算法（NSGA-II）来解决上述优化问题。以此为例，以中央直辖市电动汽车的具体数据为例。实证结果表明，采用最优定价策略，该市某天的峰谷比从56.8％降低到43％，进一步平滑了负荷曲线，减轻了负荷波动的影响。在一定程度上，对电动汽车和充电站分布不均引起的问题进行了优化。有序合理的电价策略可以指导用户调整充电习惯，确保电网安全，并确保各方的经济利益。