Подходы к исследованиям по планированию и выбору мест расположения зарядных станций для электромобилей в крупных городах

Urban electric vehicle charging station is the basic supporting facilities for electric vehicle charging and energy supply, scientific and reasonable distribution planning can provide users with the convenience of charging, and can also reduce the construction cost for the government and enterprises to obtain more profits. This paper analyses the feasibility of electric vehicle urban charging station siting and discusses the significance of electric vehicle urban charging station planning and siting for sustainable development

Simultaneous vehicle routing and charging station siting for commercial Electric Vehicles

As organizations electrify their vehicle fleets in order to lower costs, reduce emissions, and improve their pub-lic image, they face the problem of providing charging access to their vehicles on the road. Electric vehicle

Big Data for Urban Sustainability: Integrating Personal Mobility Dynamics in Environmental Assessments.

To alleviate fossil fuel use, reduce air emissions, and mitigate climate change, “new mobility” systems start to emerge with technologies such as electric vehicles, multi-modal transportation enabled by information and communications technology, and car/ride sharing. Current literature on the environmental implications of these emerging systems is often limited by using aggregated travel pattern data to characterize personal mobility dynamics, neglecting the individual heterogeneity. Individual travel patterns affect several key factors that determine potential environmental impacts, including charging behaviors, connection needs between different transportation modes, and car/ride sharing potentials. Therefore, to better understand these systems and inform decision making, travel patterns at the individual level need to be considered. Using vehicle trajectory data of over 10,000 taxis in Beijing, this research demonstrates the benefits of integrating individual travel patterns into environmental assessments through three case studies (vehicle electrification, charging station siting, and ride sharing) focusing on two emerging systems: electric vehicles and ride sharing. Results from the vehicle electrification study indicate that individual travel patterns can impact the environmental performance of fleet electrification. When battery cost exceeds $200/kWh, vehicles with greater battery range cannot continuously improve travel electrification and can reduce electrification rate. At the current battery cost of$400/kWh, targeting subsidies to vehicles with battery range around 90 miles can achieve higher electrification rate. The public charging station siting case demonstrates that individual travel patterns can better estimate charging demand and guide charging infrastructure development. Charging stations sited according to individual travel patterns can increase electrification rate by 59% to 88% compared to existing sites. Lastly, the ride sharing case shows that trip details extracted from vehicle trajectory data enable dynamic ride sharing modeling. Shared taxi rides in Beijing can reduce total travel distance and air emissions by 33% with 10-minute travel time deviation tolerance. Only minimal tolerance to travel time change (4 minutes) is needed from the riders to enable significant ride sharing (sharing 60% of the trips and saving 20% of travel distance). In summary, vehicle trajectory data can be integrated into environmental assessments to capture individual travel patterns and improve our understanding of the emerging transportation systems.PhDNatural Resources and Environment and Environmental EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113510/1/caih_1.pd

A linearized approach for the electric light commercial vehicle routing problem combined with charging station siting and power distribution network assessment

Transportation electrification has demonstrated a significant position on power utilities and logistic companies, in terms of assets operation and management. Under this context, this paper presents the problem of seeking feasible and good quality routes for electric light commercial vehicles considering battery capacity and charging station siting on the power distribution system. Different transportation patterns for goods delivery are included, such as the capacitated vehicle routing problem and the shortest path problem for the last mile delivery. To solve the problem framed within a mixed integer linear mathematical model, the GAMS software is used and validated on a test instance conformed by a 19-customer transportation network, spatially combined with the IEEE 34 nodes power distribution system. The sensitivity analysis, performed during the computational experiments, show the behavior of the variables involved in the logistics operation, i.e., routing cost for each transport pattern. The trade-off between the battery capacity, the cost of the charging station installation, and energy losses on the power distribution system is also shown, including the energy consumption cost created by the charging operation.Universidad Tecnológica de Bolíva

A review on the charging station planning and fleet operation for electric freight vehicles

Freight electrification introduces new opportunities and challenges for planning and operation. Although research on charging infrastructure planning and operation is widely available for general electric vehicles, unique physical and operational characteristics of EFVs coupled with specific patterns of logistics require dedicated research. This paper presents a comprehensive literature review to gain a better understanding of the state-of-the-art research efforts related to planning (charging station siting and sizing) and operation (routing, charge scheduling, platoon scheduling, and fleet sizing) for EFVs. We classified the existing literature based on the research topics, innovations, methodologies, and solution approaches, and future research directions are identified. Different types of methodologies, such as heuristic, simulation, and mathematical programming approaches, were applied in the reviewed literature where mathematical models account for the majority. We further narrated the specific modeling considerations for different logistic patterns and research goals with proper reasoning. To solve the proposed models, different solution approaches, including exact algorithms, metaheuristic algorithms, and software simulation, were evaluated in terms of applicability, advantages, and disadvantages. This paper helps to draw more attention to the planning and operation issues and solutions for freight electrification and facilitates future studies on EFV to ensure a smooth transition to a clean freight system.Comment: 43 pages, 4 figures, 2 table

THE PARTIALLY RECHARGEABLE ELECTRIC VEHICLE ROUTING PROBLEM WITH TIME WINDOWS AND CAPACITATED CHARGING STATIONS

Electric vehicles are potentially beneficial for both the environment and an organization\u27s bottom line. These benefits include, but are not limited to, reduced fuel costs, government tax incentives, reduced greenhouse gas emissions, and the ability to promote a company\u27s green image. In order to decide whether or not to convert or purchase electric trucks and install charging facilities, decision makers need to consider many factors including onboard battery capacity, delivery or service assignments, scheduling and routes, as well as weather and traffic conditions in a well-defined modeling framework. We develop a model to solve the partially rechargeable electric vehicle routing problem with time windows and capacitated charging stations. Given destination data and vehicle properties, our model determines the optimal number of vehicles or charging stations needed to meet the network\u27s requirements. Analyzing the model shows the relationships between vehicle range, battery recharge time, and fleet size

Charging Autonomous Electric Vehicle Fleet for Mobility-on-Demand Services: Plug in or Swap out?

This paper compares two prevalent charging strategies for electric vehicles, plug-in charging and battery swapping, to investigate which charging strategy is superior for electric autonomous mobility-on-demand (AMoD) systems. To this end, we use a queueing-theoretic model to characterize the vehicle waiting time at charging stations and battery swapping stations, respectively. The model is integrated into an economic analysis of the electric AMoD system operated by a transportation network company (TNC), where the incentives of passengers, the charging/operating shift of TNC vehicles, the operational decisions of the platform, and the planning decisions of the government are captured. Overall, a bi-level optimization framework is proposed for charging infrastructure planning of the electric AMoD system. Based on the proposed framework, we compare the socio-economic performance of plug-in charging and battery swapping, and investigate how this comparison depends on the evolving charging technologies (such as charging speed, battery capacity, and infrastructure cost). At the planning level, we find that when choosing plug-in charging, increased charging speed leads to a transformation of infrastructure from sparsely distributed large stations to densely distributed small stations, while enlarged battery capacity transforms the infrastructure from densely distributed small stations to sparsely distributed large stations. On the other hand, when choosing battery swapping, both increased charging speed and enlarged battery capacity will lead to a smaller number of battery swapping stations. At the operational level, we find that improved charging speed leads to increased TNC profit when choosing plug-in charging, whereas improved charging speed may lead to smaller TNC profit under battery swapping. The above insights are validated through realistic numerical studies