Coordinated Siting and Sizing of Electric Taxi Charging Stations Considering Traffic and Power Systems Conditions

[EN] Electric Vehicles (EVs) have gained increased attention courtesy their potential to mitigate environmental issues associated with transportation. To integrate EVs in transportation and power networks, it is essential to properly perform the siting and sizing of charging stations. In particular, this task is more challenging for users that have more rigid schedules such as taxi drivers. This paper proposes a coordinated siting and sizing methodology for electric taxi (ET) charging stations considering both transportation and power system constraints. The case of Quito, Ecuador has been analyzed. The results indicate the optimal placement of the ET charging stations and the number of charging spots to be installed.This paper belongs to the project SIS.JCG.19.03 from Universidad de las Americas-Ecuador. The authors would like to thank Irvin Cedenos from BYD E-motors Ecuador for the fruitful discussions.Clairand, J.; González-Rodríguez, M.; Kumar, R.; Vyas, S.; Escrivá-Escrivá, G. (2021). Coordinated Siting and Sizing of Electric Taxi Charging Stations Considering Traffic and Power Systems Conditions. IEEE. 1-6. https://doi.org/10.1109/PowerTech46648.2021.9495003S1

Planning of Fast Charging Infrastructure for Electric Vehicles in a Distribution System and Prediction of Dynamic Price

The increasing number of electric vehicles (EVs) has led to the need for installing public electric vehicle charging stations (EVCS) to facilitate ease of use and to support users who do not have the option of residential charging. The public electric vehicle charging infrastructures (EVCIs) must be equipped with a good number of EVCSs, with fast charging capability, to accommodate the EV traffic demand, which would otherwise lead to congestion at the charging stations. The location of these fast-charging infrastructures significantly impacts the distribution system (DS). We propose the optimal placement of fast-charging EVCIs at different locations in the distribution system, using multi-objective particle swarm optimization (MOPSO), so that the power loss and voltage deviations are kept at a minimum. Time-series analysis of the DS and EV load variations are performed using MATLAB and OpenDSS. We further analyze the cost benefits of the EVCIs under real-time pricing conditions and employ an autoregressive integrated moving average (ARIMA) model to predict the dynamic price. The simulated test system without any EVCI has a power loss of 164.36 kW and squared voltage deviations of 0.0235 p.u. Using the proposed method, the results obtained validate the optimal location of 5 EVCIs (each having 20 EVCSs with a 50kWh charger rating) resulting in a minimum power loss of 201.40 kW and squared voltage deviations of 0.0182 p.u. in the system. Significant cost benefits for the EVCIs are also achieved, and an R-squared value of dynamic price predictions of 0.9999 is obtained. This would allow the charging station operator to make promotional offers for maximizing utilization and increasing profits

Development of the Plug-in Electric Vehicle Charging Infrastructure via Smart-Charging Algorithms

Electricity generation and the transportation sector make up a large portion of greenhouse gas emissions in the United States. Meeting ambitious reductions in greenhouse gasses requires large scale adoption of plug-in electric vehicles (PEVs) and has led to several policies and laws aimed at incentivizing PEV sales. An inadequate charging infrastructure, however, could be a major obstacle for a large-scale adoption of PEVs. Large electrical demands from PEVs could negatively affect circuitry, increase electricity costs, and exacerbate stress to local electrical components during times of high electricity usage. These issues, however, can be addressed by deploying smart-charging strategies.This work is focused on the development of smart-charging protocols for workplace battery electric vehicle (BEV) charging. Three comprehensive smart-charging protocols with different applications are proposed. Each protocol is developed with varying degrees of focus on communication requirements and privacy concerns. The BEV-based Optimization Protocol is a decentralized, non-iterative strategy that allows BEVs to individually schedule their charging schedules. The Octopus Charger-based MILP Protocol allows octopus chargers (i.e., charging stations with multiple cables) to independently schedule charging for their assigned BEVs. The Real-Time Octopus Charger-based MILP Protocol allows octopus chargers to schedule BEV charging in real time, without prior information from BEVs. By using the appropriate cost signal and assignment algorithms, the proposed protocols can manage a parking structure demand load while reducing the number of installed charging stations. Driving patterns from the National Household Travel Survey were used to perform simulations, to verify and quantify the effectiveness of each protocol. The proposed protocols resulted in improved peak load reductions for all simulated smart-charging scenarios, when compared with uncontrolled charging. By using octopus chargers, all protocols were able to reduce the number of charging stations needed at parking structures, while meeting the charging requests of all BEVs. Time-Of-Use rate plans from Southern California Edison were used to estimate monthly electricity costs for the simulated parking structures. The smart-charging protocols resulted in reduced electricity costs for most cases studied, when compared to uncontrolled charging

Optimizing urban charging infrastructure for shared electric vehicles

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 115-117).This thesis analyses the opportunities and constraints of deploying charging infrastructure for shared electric vehicles in urban environments. Existing electric vehicle charging infrastructure for privately owned vehicles is examined and critiqued. A prototype of smartCharge, an integrated locking, charging, and ambient information system for shared electric vehicles is presented. Design methodology, fabrication of mechanical and electrical systems, and testing of the smartCharge system is documented. Urban implementation case studies for such a universal charging and locking station illustrate the potential of optimized infrastructure for shared vehicles to transform urban streetscapes and improve mobility. An analysis of leveraging existing building electrical infrastructure for vehicle charging is conducted, including phasing strategies for deploying rapid charging. Technological constraints to rapid charging such as battery chemistry, pack design, and power input are presented and evaluated. A strategy for buffering rapid electric vehicle charging with commercial uninterruptible power supply (UPS) systems is described. Two recent buildings on the MIT campus are used as case studies to demonstrate the overhead transformational capacity that exists in many modem, multi-purpose buildings. Connectivity between electrified transport, the electrical grid, and renewable energy sources is explored. A vision for personal urban mobility enabled by fleets of shared electric vehicles powered by clean, renewable energy and intelligent charging infrastructure is proposed.by Praveen Subramani.S.M

Electric vehicles charging infrastructure demand and deployment : challenges and solutions

Present trends indicate that electrical vehicles (EVs) are favourable technology for road network transportation. The lack of easily accessible charging stations will be a negative growth driver for EV adoption. Consequently, the charging station placement and scheduling of charging activity have gained momentum among researchers all over the world. Different planning and scheduling models have been proposed in the literature. Each model is unique and has both advantages and disadvantages. Moreover, the performance of the models also varies and is location specific. A model suitable for a developing country may not be appropriate for a developed country and vice versa. This paper provides a classification and overview of charging station placement and charging activity scheduling as well as the global scenario of charging infrastructure planning. Further, this work provides the challenges and solutions to the EV charging infrastructure demand and deployment. The recommendations and future scope of EV charging infrastructure are also highlighted in this paper