动态能源与地理信息融合的光储充电站电动汽车充电路径引导

电动汽车(EV)的出行、充电行为在对交通系统运行规律造成影响的同时，也使得能源网络负荷的时空分布发生改变。为此，考虑光储充一体化系统的特点，结合大规模EV、区域路网、配电网以及光储充电站的动态信息，构建了精细化的车-站-路-网动态融合模型；在此基础上，分别从用户、交通路网、电网3个角度构建包含行程时间、交通拥堵情况、电网稳定性的多目标优化函数。针对当前模型的高复杂度，运用分层规划和双向搜索思路对LPA*路径规划算法进行改进，从而实现动态环境下的充电路径引导。以某市一区域路网为例进行仿真，结果表明：与现有的策略相比，所提充电路径引导策略能很好地解决因EV充电带来的局部道路拥挤、区域光储能源消纳不均衡等问题。

Charging path guidance of electric vehicles at photovoltaic-storage charging stations based on dynamic energy and geographic information fusion

The traveling behavior and charging behavior of electric vehicles(EVs) not only affect the operation law of transportation system, but also change the spatial and temporal distribution of energy network load. Therefore, considering the characteristics of the photovoltaic-storage-charging integrated system and combined with the dynamic information of large-scale EVs, regional road network, distribution network and photovoltaic-storage charging stations, a refined EV-station-road-network dynamic fusion model is constructed. On this basis, a multi-objective optimization function is constructed from three perspectives of users, traffic network and power grid, which includes the travel time, the traffic congestion and the power grid stability. Aiming at the high complexity of the current model, the LPA* path planning algorithm is improved by using the hierarchical programming and bidirectional search, so as to realize the charging path guidance under dynamic environment. Taking a regional road network in a city as an example, the simulative results show that compared with the existing strategies, the proposed charging path guidance strategy can well solve the problems caused by EV charging, such as local road congestion, uneven consumption of regional photovoltaic-storage energy, and so on.