Designing electric vehicle charging infrastructure to enable disaster evacuation

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Date

2022-08-11

Authors

Lu, Le, 1996-

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Abstract

Natural disasters such as hurricanes can cause widespread power outages and force thousands of people to physically evacuate an affected area. As electric vehicle (EV) adoption grows, ensuring that residents can successfully evacuate during a disaster could become a significant problem. In this study, we develop a Two-Stage Stochastic Program (TSSP) to optimally allocate EV charging infrastructure within a road network to enable disaster evacuations, and then route EVs to safe zones. The objective considers both how many EVs are successfully moved to safe zones and how quickly they reach them, subject to a budget constraint, with charging investments in the first stage, and energy-limited EV routing in the second stage. Uncertainties in our model include the time when people start to evacuate and the severity of the hurricane. We parameterize our model to study the evacuation of the Houston-Galveston region of Texas, an area that is highly vulnerable to hurricanes. Over 50 random scenarios and assuming half of the area's vehicles are EVs, we find that on average 92.4% of EVs are able to evacuate within a 12-hour evacuation window, with a $10 million charging budget, our "high" charge level distribution, and EVs with 195 miles of range. Nodes with large populations, at major intersections, or along key routes to safe zones are particularly attractive targets for installing EV charging capacity. In scenarios where more of the EVs must seek charging during the evacuation, the model's charging allocations are more heavily concentrated on these nodes. We also discover that the model returns more evenly spread out - and therefore, perhaps more realistic - charging station investments with a longer evacuation window (24 hours) than a shorter window (12 hours). Finally, we find that having EVs pre-charged at the start of the evacuation process is crucial and it significantly improves the performance of the evacuation process.

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