住宅小区充电站电动汽车有序充电方法

Orderly charging method of electric vehicle in charging station of residential area

中文关键词: 电动汽车  数据挖掘技术  模糊C均值聚类算法  马尔科夫链  有序充电

英文关键词: electric vehicle  advanced data mining technology  fuzzy C ⁃ means clustering algorithm  Markov chain  orderly charging

中文摘要:

      对充满随机性的电动汽车进行有序充电管理，是当今“绿色出行”时代亟待解决的问题。基于数据挖掘技术首先建立起电动汽车的数学模型，以北京市某小区电动汽车出行历史数据为例，利用模糊C均值聚类算法对车主的行驶行为、入网电动汽车的初始电池荷电状态进行分析，把握电动汽车负荷特性。基于马尔科夫链的思想建立由精炼后的多条典型电动汽车负荷模式转移概率矩阵组成的模型，对电动汽车的随机动态变化过程进行描述，并应用多种群遗传算法求解电动汽车的有序充电问题。以小区充电站为例，并与其他方法进行对比，验证了本文模型和方法的有效性。

英文摘要:

      How to orderly charge electric vehicles with randomness is an urgent problem to be solved in“green travel”period today. Firstly, a mathematical model of electric vehicles based on advanced data mining technology is established. To grasp the load characteristics of the electric vehicle, the fuzzy C-means clustering algorithm is used to analyze the driving behavior of the owner and the initial battery state of the incoming electric vehicle taking the historical data of electric vehicle travel in a community in Beijing as an example. Based on the idea of Markov chain, a model consisting of several typical electric vehicle load mode transition probability matrices is established to describe the stochastic dynamic process of electric vehicles. Multiple population GA is applied to solve the orderly charging problem of electric vehicles.Taking the community charging station as an example and comparing with other methods, the effectiveness of the model and method is verified.