Dynamic charging of electric vehicles integrating renewable energy: a multi-objective optimisation problem
Dynamic charging of electric vehicles integrating renewable energy: a multi-objective optimisation problem
复制标题
集成可再生能源的电动汽车动态充电：多目标优化问题
DOI：
10.1049/iet-stg.2018.0066
复制
发表时间：
2019
期刊：
影响因子：
2.3
通讯作者：
Humfrey H
中科院分区：
文献类型：
--
作者：
Humfrey H
动态充电电动汽车（EV）有可能显着降低里程焦虑，并减少可接受范围所需的电池尺寸。然而，随着电动汽车技术进步的主要驱动力是减少碳排放，需要考虑动态充电系统将如何影响这些排放。本研究提出了一种需求侧管理方法，用于动态分配资源，以考虑当地可再生能源发电的整合。一个多目标优化问题，制定考虑个人用户，能源零售商和监管机构的球员有冲突的利益。与先到先得的分配方法相比，在24小时内观察到从电网中提取的能量减少了19%。考虑到每个时间间隔的电网组成，这导致二氧化碳排放量减少22%。此外，与没有本地可再生能源集成的系统相比，二氧化碳排放量减少了42%。通过改变分配给玩家目标的权重，该方法可以减少高峰时段的总体需求，并产生更平滑的需求曲线。系统的公平性得到改善，平均基尼系数降低4.32%。
Dynamically charging electric vehicles (EVs) have the potential to significantly reduce range anxiety and decrease the size of battery required for acceptable range. However, with the main driver for progressing EV technology being the reduction of carbon emissions, consideration of how a dynamic charging system would impact these emissions is required. This study presents a demand‐side management method for allocating resources to charge EVs dynamically considering the integration of local renewable generation. A multi‐objective optimisation problem is formulated to consider individual users, an energy retailer and a regulator as players with conflicting interests. A 19% reduction in the energy drawn from the power grid is observed over the course of a 24 h period when compared with a first‐come‐first‐served allocation method. This results in a greater reduction in CO2emissions of 22% by considering the power grid's make‐up at each time interval. Furthermore, a 42% reduction in CO2emissions is achieved compared to a system without local renewable energy integration. By varying the weights assigned to the players’ goals, the method can reduce overall demand at peak times and produce a smoother demand profile. System fairness is shown to improve with an average Gini coefficient reduction of 4.32%.