In order to investigate further the

In order to investigate further the system performance in a large-scale scenario, the evolution of a portion of the grid characterized by a maximum available power of 6 MW during an 8-h period was also analyzed. Statistical simulations were performed for 10 different cases in which the arrivals of the users were modelled by using Poisson distributions with a mean value of 100 per 30 min, and random charging profiles were assumed. The analysis of the process was carried out by considering the three different efficiency profiles assumed in the previous analysis. The values of the utility profit obtained by using the SEWP and the MEWP approaches are 9210D and 8811D , respectively. Simulation results related to the average degree of user satisfaction in the different scenarios considered are summarized in Table 5. The data in the table evidence that, also in a large-scale scenario, although the two strategies show similar performances when a constant unitary efficiency is considered, the SEWP approach performs significantly better than the MEWP one in the presence of variable charging efficiency profiles. As shown, taking into account the relationship between the
charging efficiency and the charging rate is therefore crucial when aiming to develop effective variable-rate-based charging strategies.The study, which has been carried out by comparing two strategies taken as examples, can be also applied in order to evaluate the real effectiveness of any other possible charging method. Thus,the analysis performed gives useful well-founded guidelines forthe development of smart charging strategies for PEVs, as well as
for next-generation battery charging and smart grid management systems.

結果 (中文) 1:

In order to investigate further the system performance in a large-scale scenario, the evolution of a portion of the grid characterized by a maximum available power of 6 MW during an 8-h period was also analyzed. Statistical simulations were performed for 10 different cases in which the arrivals of the users were modelled by using Poisson distributions with a mean value of 100 per 30 min, and random charging profiles were assumed. The analysis of the process was carried out by considering the three different efficiency profiles assumed in the previous analysis. The values of the utility profit obtained by using the SEWP and the MEWP approaches are 9210D and 8811D , respectively. Simulation results related to the average degree of user satisfaction in the different scenarios considered are summarized in Table 5. The data in the table evidence that, also in a large-scale scenario, although the two strategies show similar performances when a constant unitary efficiency is considered, the SEWP approach performs significantly better than the MEWP one in the presence of variable charging efficiency profiles. As shown, taking into account the relationship between the当旨在发展有效的基于可变速率的收费策略，充电效率和充电率因此十分重要。研究，进行了通过比较两种策略为例，也可为真实评价的任何其他可能的收费方法。因而，进行的分析给有用的确凿指引发展的智能收费策略为学券计划，以及下一代电池充电和智能电网管理系统。

結果 (中文) 3:

为了进一步研究在一个大型的情况下系统的性能，并分析了网格的特点是6兆瓦的最大可用功率8小时期间的一部分演变。统计模拟进行10种不同的情况下，用户的人数分别采用泊松分布的平均值为100每30分钟，和随机充电曲线假设。从三个不同的效率分布的假定分析进行分析的过程中。利用sewp和初步分析的方法9210d和8811d获得的效用利润值，分别。仿真结果在不同的情况下考虑用户的平均满意度相关总结在表5。表中的数据表明，在一个大型的情况下，虽然两策略显示出类似的表现时，常被认为是单一的效率，的sewp方法明显优于初步分析1中存在的可变充电效率曲线。如图所示，考虑到关系的
充电效率和充电率是至关重要的，旨在发展之间有效的变率计费策略的研究，这是通过比较两种策略为例进行的，也可以适用于以评估其他可能的充电方法的实际效果。因此，进行的分析提供了有用的成立为发展策略指引的智能电动汽车充电，以及
下一代电池充电和智能电网管理系统。