工程科学与技术2017，Vol.49Issue(3)：170-178,9.DOI:10.15961/j.jsuese.201600357
基于马尔科夫链充电负荷预测的多区域充电桩优化配置研究
Optimal Allocation of Charging Piles in Multi-areas Considering Charging Load Forecasting Based on Markov Chain
摘要
Abstract
Considering the complexity and diversity of customers' travel habits,the charging piles need to be allocated appropriately to satisfy the charging demand.Firstly,Markov chain is used to describe the variation of battery state of charge on electric vehicle owners' trip in the whole day,according to three decision-making behavior including driving,charging,neither charging nor driving.Then the real-time charging behavior in the process could be determinated,which indicates the fast and slow charging demand of different vehicle types.Considering mobility characteristics of electric vehicles and the number of different types of electric vehicles in different time periods in some area,the total load demand could be forecasted.The optimal allocation model for charging piles is proposed and aims to minimize investment and operating costs for the charging piles.The mobility characteristics of electric vehicles are integrated into the constraints,and the model is solved by the particle swarm optimization algorithm.The effectiveness and feasiblility of the proposed method are verified by the 33-bus four-area case study on the charging load forecasting and optimal allocation of charing piles.关键词
电动汽车/马尔科夫链/负荷需求/移动特性/充电桩Key words
electric vehicle/Markov chain/charging demand/mobility characteristics/charging piles分类
信息技术与安全科学引用本文复制引用
吕林,许威,向月,张逸,熊军..基于马尔科夫链充电负荷预测的多区域充电桩优化配置研究[J].工程科学与技术,2017,49(3):170-178,9.基金项目
国家自然科学基金资助项目(51377111) （51377111）
四川省科技厅应用基础项目资助(2015JY0128) （2015JY0128）
四川大学引进人才科研启动经费资助项目(20822041A4161) （20822041A4161）
国家电网总部科技项目资助 （）
