To accelerate adoption of non-residential charging for electric vehicles, sites must maximize utilization of existing electrical infrastructure. In this study we model electric vehicle charging at a workplace using real charging data and evaluate the lifetime of the site’s transformer as the number of charging stations is incrementally increased. We implement and compare a range of control schemes for workplace charging including minimizing the peak load, capping the total load, minimizing bills under different rate structures with time-of-use energy costs and demand charges, and directly minimizing the transformer’s aging. These are compared by the number of vehicles they allow the transformer to support, the transformer’s health, and the operator’s electricity bill. We draw a connection between minimizing the peak load and improving the transformer’s health. We observe that minimizing the electricity bill is the best scheme by both criteria when the bill includes a demand charge; in our experiment it allowed the infrastructure to support over 67% more cars than under uncontrolled charging. To protect the transformer we recommend that demand charges or capacity management be applied to parking lots of charging electric vehicles with high infrastructure utilization, and operators schedule charging to minimize their electricity bills.

为了加快采用电动汽车的非住宅充电方式，站点必须最大限度地利用现有的电子基础设施。在本研究中，我们使用真实的充电数据对工作场所中的电动汽车充电进行建模，并随着充电站数量的增加来评估站点变压器的寿命。我们实施并比较了一系列用于工作场所充电的控制方案，包括最大程度地减少峰值负载，限制总负载，将不同费率结构下的票据与使用时间的能源成本和需求费用一起最小化，并直接将变压器的老化最小化。将它们与允许变压器支持的车辆数量，变压器的健康状况以及操作员的电费进行比较。我们在最小化峰值负载和改善变压器的健康之间建立了联系。我们观察到，当电费中包含需求费用时，从这两个标准来看，将电费降至最低是最佳方案。在我们的实验中，与不受控制的充电相比，它可以使基础设施支持的汽车多出67％。为了保护变压器，我们建议对基础设施利用率高的电动汽车停车场进行按需收费或容量管理，并且运营商应安排充电以最大程度地减少电费。