Under the pressure of climate change, the transportation sector is under electrification, and electric vehicles (EVs) are encouraged to reduce their reliance on fossil fuels. However, in those regions where coal is a dominating power generation fuel source, different opinions about whether EVs can help emission reduction exist. In other words, whether EVs can help emission reduction depends on the energy system configuration and the power generation mix. To achieve the overall emission reduction in both systems, a collaborative planning strategy for electricity and transportation systems is proposed. In the electricity distribution network, the renewable energy source is planned to cope with future demand growth due to the increasing use of EVs. In the transportation network, hydrogen fuel cell vehicles (FCVs) are introduced to realize the coordinated development of different types of vehicles. The location of the hydrogen refueling stations can be planned, and the penetration ratio of internal combustion vehicles, EVs, and FCVs is optimized. The proposed planning model is verified on the 46-bus electricity distribution network and the 21-bus transportation network. The mixed-integer linear programming (MILP) and subgradient methods are employed to solve the proposed optimization model. According to the simulation results, the proposed model can achieve the lowest emission since the electricity and transportation systems can cooperate well.

中文翻译：

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考虑氢燃料电池汽车的配电网与交通系统协同规划

在气候变化的压力下，交通部门正在电气化，鼓励电动汽车（EV）减少对化石燃料的依赖。然而，在以煤炭为主要发电燃料来源的地区，对于电动汽车是否有助于减排存在不同意见。换言之，电动汽车能否帮助减排取决于能源系统配置和发电结构。为了实现两个系统的整体减排，提出了电力和交通系统的协同规划策略。在配电网络中，计划使用可再生能源来应对因电动汽车使用量增加而导致的未来需求增长。在交通网络中，引入氢燃料电池汽车（FCV），实现不同类型汽车的协同发展。可规划加氢站位置，优化内燃汽车、电动汽车、燃料电池汽车的普及率。所提出的规划模型在 46 总线配电网络和 21 总线运输网络上进行了验证。混合整数线性规划（MILP）和次梯度方法被用来解决所提出的优化模型。根据仿真结果，由于电力和交通系统可以很好地配合，所提出的模型可以实现最低排放。并且优化了燃料电池汽车。所提出的规划模型在 46 总线配电网络和 21 总线运输网络上进行了验证。混合整数线性规划（MILP）和次梯度方法被用来解决所提出的优化模型。根据仿真结果，由于电力和交通系统可以很好地配合，所提出的模型可以实现最低排放。并且优化了燃料电池汽车。所提出的规划模型在 46 总线配电网络和 21 总线运输网络上进行了验证。混合整数线性规划（MILP）和次梯度方法被用来解决所提出的优化模型。根据仿真结果，由于电力和交通系统可以很好地配合，所提出的模型可以实现最低排放。