This study proposes a novel disruption prevention model that considers both long-term expansion decisions and short-term operational decisions to design and manage an electric vehicle charging station network under power demand uncertainty. A non-linear term is introduced into the model to prevent the evolution of excessive temperature on a power line under different exogenous factors (e.g., outside temperature, air velocity). We first linearize the model using extensions of McCormick relaxation technique and then solve using a combined Sample Average Approximation with a Scenario Decomposition algorithm. A real life case study is presented to draw a several key managerial insights. It is observed that the disruption prevention model is able to reduce 16% overall system cost upon a power outage. The results of the analysis help decision-makers achieving a more reliable and cost-effective electricity supply network.

这项研究提出了一种新颖的防干扰模型，该模型同时考虑了长期扩展决策和短期运营决策，以在电力需求不确定的情况下设计和管理电动汽车充电站网络。非线性项被引入到模型中，以防止在不同的外在因素（例如外部温度，空气速度）下电力线上过高的温度演变。我们首先使用McCormick松弛技术的扩展来线性化模型，然后使用结合了场景平均分解算法的样本平均逼近来求解。提出了一个现实生活中的案例研究，以得出一些关键的管理见解。可以观察到，防中断模型能够在停电时降低16％的整体系统成本。