With the advanced communication, computation, control and manufacturing technologies, electric vehicles have been extensively developed to improve the utilization of clean energy and reduce emissions. Despite the tremendous advantages, the rapidly growing of deploying electric vehicles will bring new insecurities, such as disorderly charging behaviors, which affect the stability of the smart grid. Although considerable efforts on charging schedules have been developed to improve energy utilization and reduce load fluctuation in the smart grid, the profits of utility company have not been investigated. In addition, most of these schemes also lead to inefficient battery utilization, i.e., electric vehicles usually charge while their batteries still have a lot of energy left. To address these issues, in this paper, a novel underfill-SOC based charging pricing (USoCP) scheme is proposed for electric vehicles in smart grid, which can achieve great battery utilization, as well as guarantee great profits of utility company and load balance of the whole grid. Particularly, via introducing the Logistic function into charging pricing determination, the proposed USoCP scheme can effectively improve the underfill state of charge (underfill-SOC) for battery charging, thereby improving the battery utilization. Meanwhile, to reduce the load fluctuation and guarantee great profits of utility company, a charging price based demand-response model is conducted to determine the effective charging power quantity, and a charging pricing determination model is formalized as an optimization problem to reduce the peak-to-average ratio of power load and guarantee great electricity selling profits of utility company. Finally, a Particle Swarm Optimization (PSO) based solution is proposed to solve the optimization problem and determine the effective charging price for electric vehicles. Via extensive evaluations, the results show that the proposed USoCP scheme can effectively stimulate electric vehicles to charge more energy in each battery charging (i.e., improving the battery utilization), reduce peak power load, as well as guarantee great profits of utility company.

凭借先进的通信、计算、控制和制造技术，电动汽车得到了广泛的发展，以提高清洁能源的利用率并减少排放。尽管具有巨大的优势，但电动汽车的快速部署将带来新的不安全因素，例如无序充电行为，影响智能电网的稳定性。尽管已经在充电计划方面做出了相当大的努力，以提高能源利用率并减少智能电网的负载波动，但尚未调查公用事业公司的利润。此外，这些方案大多还导致电池利用率低下，即电动汽车通常在充电时电池仍有大量剩余电量。为了解决这些问题，在本文中，针对智能电网中的电动汽车，提出了一种新的基于底部填充 SOC 的充电定价（USoCP）方案，该方案可以实现高电池利用率，同时保证公用事业公司的丰厚利润和整个电网的负载平衡。特别是，通过在充电定价确定中引入 Logistic 函数，所提出的 USoCP 方案可以有效改善电池充电的充电不足状态（underfill-SOC），从而提高电池利用率。同时，为了减少负荷波动，保证公用事业公司的丰厚利润，采用基于充电价格的需求响应模型来确定有效充电电量，将充电定价确定模型形式化为优化问题，以降低电力负荷峰均比，保证公用事业公司可观的售电利润。最后，提出了基于粒子群优化 (PSO) 的解决方案来解决优化问题并确定电动汽车的有效充电价格。通过广泛的评估，结果表明，所提出的 USoCP 方案可以有效地刺激电动汽车在每次充电时充电更多的能量（即提高电池利用率），降低峰值电力负荷，并保证公用事业公司的丰厚利润。提出了基于粒子群优化（PSO）的解决方案来解决优化问题并确定电动汽车的有效充电价格。通过广泛的评估，结果表明，所提出的 USoCP 方案可以有效地刺激电动汽车在每次充电时充电更多的能量（即提高电池利用率），降低峰值电力负荷，并保证公用事业公司的丰厚利润。提出了基于粒子群优化（PSO）的解决方案来解决优化问题并确定电动汽车的有效充电价格。通过广泛的评估，结果表明，所提出的 USoCP 方案可以有效地刺激电动汽车在每次充电时充电更多的能量（即提高电池利用率），降低峰值电力负荷，并保证公用事业公司的丰厚利润。