Online welfare maximization for electric vehicle charging with electricity cost
Online welfare maximization for electric vehicle charging with electricity cost
复制标题
DOI：
10.1145/2602044.2602053
复制
发表时间：
2014-06
期刊：
影响因子：
--
通讯作者：
Zizhan Zheng;N. Shroff
中科院分区：
文献类型：
--
作者：
Zizhan Zheng;N. Shroff
过去几年电动汽车的加速普及引发了人们的担忧，即当大量电动汽车同时充电时，电网可能会过载。利用充电请求的时间弹性，实现电动汽车在公共设施的大规模自动充电调度是一个很有前景的方向。本文研究了以服务车辆总价值减去所产生的能源成本为目标的电动汽车在线充电问题。不同于以往的研究大多只考虑固定容量约束而忽略电力成本，本文对系统运营者采用凸成本模型，对车主采用凹成本模型。我们设计了一种在线算法来平衡这两者，并证明了其竞争性能的界对于一类一般的估值和成本函数。
The accelerated adoption of EVs in the last few years has raised concerns that the power grid can get overloaded when a large number of EVs are charged simultaneously. A promising direction is to implement large scale automated scheduling of EV charging at public facilities, by exploiting the time elasticity of charging requests. In this work, we study the problem of online EV charging for maximizing the total value of served vehicles minus the energy cost incurred. In contrast to most previous works that assume a fixed capacity constraint while ignoring the electricity cost, we adopt a convex cost model for the system operator together with a concave valuation model for the vehicle owners. We design an online algorithm for balancing the two and prove a bound on its competitive performance for a general class of valuation and cost functions.