Elangovan Raghul, Kanwhen Ondrea, Dong Ziqian, Mohamed Ahmed, Rojas-Cessa Roberto
Networking and Innovation Laboratory, Department of Electrical and Computer Engineering, College of Engineering and Computing Sciences, New York Institute of Technology, New York, NY, United States.
Smart Grid Interdependencies Laboratory, Department of Electrical Engineering, City University of New York City College, New York, NY, United States.
Front Big Data. 2021 Jul 26;4:693820. doi: 10.3389/fdata.2021.693820. eCollection 2021.
New York City's food distribution system is among the largest in the United States. Food is transported by trucks from twelve major distribution centers to the city's point-of-sale locations. Trucks consume large amounts of energy and contribute to large amounts of greenhouse gas emissions. Therefore, there is interest to increase the efficiency of New York City's food distribution system. The Gowanus district in New York City is undergoing rezoning from an industrial zone to a mix residential and industrial zone. It serves as a living lab to test new initiatives, policies, and new infrastructure for electric vehicles. We analyze the impact of electrification of food-distribution trucks on greenhouse gas emissions and electricity demand in this paper. However, such analysis faces the challenges of accessing available and granular data, modeling of demands and deliveries that incorporate logistics and inventory management of different types of food retail stores, delivery route selection, and delivery schedule to optimize food distribution. We propose a framework to estimate truck routes for food delivery at a district level. We model the schedule of food delivery from a distribution center to retail stores as a vehicle routing problem using an optimization solver. Our case study shows that diesel trucks consume 300% more energy than electric trucks and generate 40% more greenhouse gases than diesel trucks for food distribution in the Gowanus district.
纽约市的食品配送系统是美国最大的系统之一。食品通过卡车从十二个主要配送中心运往该市的销售点。卡车消耗大量能源，并产生大量温室气体排放。因此，人们有兴趣提高纽约市食品配送系统的效率。纽约市的高瓦纳斯区正在从工业区重新规划为住宅和工业区混合的区域。它作为一个生活实验室，用于测试电动汽车的新举措、政策和新基础设施。在本文中，我们分析了食品配送卡车电动化对温室气体排放和电力需求的影响。然而，此类分析面临着获取可用的详细数据、对包含不同类型食品零售店的物流和库存管理的需求及配送进行建模、选择配送路线以及安排配送时间表以优化食品配送等挑战。我们提出了一个在区域层面估算食品配送卡车路线的框架。我们使用优化求解器将从配送中心到零售店的食品配送时间表建模为车辆路径问题。我们的案例研究表明，在高瓦纳斯区进行食品配送时，柴油卡车比电动卡车多消耗300%的能源，产生的温室气体比电动卡车多40%。
