scholarly journals Autonomous Transport Innovation (ATI) : integration of autonomous electric vehicles into a tactical microgrid

2021 ◽  
Author(s):  
Angela Rolufs ◽  
Amelia Trout ◽  
Kevin Palmer ◽  
Clark Boriack ◽  
Bryan Brilhart ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Research Area ◽  
Electric Transport ◽  
Vehicle To Grid ◽  
Operational Testing ◽  
Military Applications ◽  
Operational Tests ◽  
Transportation Technologies ◽  
Support Research ◽  
Autonomous Electric Vehicles

The objective of the Autonomous Transport Innovation (ATI) technical research program is to investigate current gaps and challenges then develop solutions to integrate emerging electric transport vehicles, vehicle autonomy, vehicle-to-grid (V2G) charging and microgrid technologies with military legacy equipment. The ATI research area objectives are to: identify unique military requirements for autonomous transportation technologies; identify currently available technologies that can be adopted for military applications and validate the suitability of these technologies to close need gaps; identify research and operational tests for autonomous transport vehicles; investigate requirements for testing and demonstrating of bidirectional vehicle charging within a tactical environment; develop requirements for a sensored, living laboratory that will be used to assess the performance of autonomous innovations; and integrate open standards to promote interoperability and broad-platform compatibility. The research performed resulted in an approach to develop a sensored, living laboratory with operational testing capability to assess the safety, utility, interoperability, and resiliency of autonomous electric transport and V2G technologies in a tactical microgrid. The living laboratory will support research and assessment of emerging technologies and determine the prospect for implementation in defense transport operations and contingency base energy resilience.

scholarly journals Integration of autonomous electric transport vehicles into a tactical microgrid : final report

2021 ◽  
Author(s):  
Angela Rolufs ◽  
Amelia Trout ◽  
Kevin Palmer ◽  
Clark Boriack ◽  
Bryan Brilhart ◽  
...  
Keyword(s):  
Research Area ◽  
Final Report ◽  
Electric Transport ◽  
Vehicle To Grid ◽  
Operational Testing ◽  
Military Applications ◽  
Operational Tests ◽  
Open Standards ◽  
Transportation Technologies ◽  
Support Research

The objective of the Autonomous Transport Innovation (ATI) technical research program is to investigate current gaps and challenges and develop solutions to integrate emerging electric transport vehicles, vehicle autonomy, vehicle-to-grid (V2G) charging and microgrid technologies with military legacy equipment. The ATI research area objectives are to: identify unique military requirements for autonomous transportation technologies; identify currently available technologies that can be adopted for military applications and validate the suitability of these technologies to close need gaps; identify research and operational tests for autonomous transport vehicles; investigate requirements for testing and demonstrating of bidirectional-vehicle charging within a tactical environment; develop requirements for a sensored, living laboratory that will be used to assess the performance of autonomous innovations; and integrate open standards to promote interoperability and broad-platform compatibility. This final report summarizes the team’s research, which resulted in an approach to develop a sensored, living laboratory with operational testing capability to assess the safety, utility, interoperability, and resiliency of autonomous electric transport and V2G technologies in a tactical microgrid. The living laboratory will support research and assessment of emerging technologies and determine the prospect for implementation in defense transport operations and contingency base energy resilience.

scholarly journals Application Design Aiming to Minimize Drivers’ Trip Duration through Intermediate Charging at Public Station Deployed in Smart Cities

2019 ◽  
Vol 10 (4) ◽  
pp. 67
Author(s):  
Ibrahim El-Fedany ◽  
Driss Kiouach ◽  
Rachid Alaoui
Keyword(s):  
Electric Vehicles ◽  
Smart Cities ◽  
Limited Range ◽  
Electric Transport ◽  
Charging Infrastructure ◽  
Vehicle To Grid ◽  
The Road ◽  
Smart Charging ◽  
Grid Applications ◽  
On The Road

Today, smart cities are turning to electric transport, carpooling and zero emission zones. The growing number of electric vehicles on the roads makes it increasingly necessary to have a public charging infrastructure. On the other hand, the main limitations of electric vehicles are the limited range of their batteries and their relatively long charging times. To avoid having problems to recharge, electric vehicle drivers must plan their journeys more thoroughly than others. At the goal of optimizing trip time, drivers need to automate their travel plans based on a smart charging solution, which will require the development of new Vehicle-to-Grid applications that will allow at the charging stations to dynamically interact with the vehicles. In this paper, we propose an architecture based on an algorithm allowing the management of charging plans for electric vehicles traveling on the road to their destination, in order to minimize the duration of the drivers’ journey including waiting and charging times. The decision taken by the algorithm based on the exploration of the data of each public supply station according to its location, number of vehicles in the queue, number of charging sockets, and rates of service.

scholarly journals Analysis of EV Cost-Based Charging Load Profiles

Proceedings ◽  
2020 ◽  
Vol 65 (1) ◽  
pp. 2
Author(s):  
Elisavet Koutsi ◽  
Sotirios Deligiannis ◽  
Georgia Athanasiadou ◽  
Dimitra Zarbouti ◽  
George Tsoulos
Keyword(s):  
Electric Vehicles ◽  
User Preferences ◽  
Reference Scenario ◽  
Electricity Prices ◽  
Horizon 2020 ◽  
Vehicle To Grid ◽  
Electrical Grid ◽  
Incentive Strategies ◽  
Grid Load ◽  
The Impact

During the last few decades, electric vehicles (EVs) have emerged as a promising sustainable alternative to traditional fuel cars. The work presented here is carried out in the context of the Horizon 2020 project MERLON and targets the impact of EVs on electrical grid load profiles, while considering both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operation modes. Three different charging policies are considered: the uncontrolled charging, which acts as a reference scenario, and two strategies that fall under the umbrella of individual charging policies based on price incentive strategies. Electricity prices along with the EV user preferences are taken into account for both charging (G2V) and discharging (V2G) operations, allowing for more realistic scenarios to be considered.

scholarly journals Privileging Electric Vehicles as an Element of Promoting Sustainable Urban Mobility—Effects on the Local Transport System in a Large Metropolis in Poland

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3838
Author(s):  
Marta Borowska-Stefańska ◽  
Michał Kowalski ◽  
Paulina Kurzyk ◽  
Miroslava Mikušová ◽  
Szymon Wiśniewski
Keyword(s):  
Transport System ◽  
Electric Vehicles ◽  
Traffic Management ◽  
Negative Impact ◽  
Software Tool ◽  
Research Area ◽  
Shopping Centre ◽  
Local Transport ◽  
Sustainable Urban Mobility ◽  
The Impact

The main purpose of this article was to determine the impact on the equilibrium of the local transport system from privileging EVs by permitting them to use bus lanes. The study used two sets of data: information on infrastructure and traffic management; and information on the recorded road network loads and traffic volumes generated by a given shopping centre—the E. Leclerc shopping centre (an important traffic generator within the city of Łódź, Poland). These sets were then used to develop a microsimulation traffic model for the shopping centre and the associated effects on the localised transport system. The model was constructed by means of the PTV Vissim software tool. An initial simulation was conducted that formed a basis for subsequent scenarios (in total, 17 simulations were performed). On the basis of the conducted analyses, it was established that—for the researched part of the transport system—privileging the still rather uncommon battery electric vehicles (BEVs) engendered a marginal deterioration of traffic conditions. At the same time, allowing BEVs to use bus lanes within the chosen research area had no negative impact on bus journey times.

scholarly journals To Represent Electric Vehicles in Electricity Systems Modelling—Aggregated Vehicle Representation vs. Individual Driving Profiles

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 539
Author(s):  
Maria Taljegard ◽  
Lisa Göransson ◽  
Mikael Odenberger ◽  
Filip Johnsson
Keyword(s):  
Electric Vehicles ◽  
Investment Model ◽  
Research Issues ◽  
Charging Infrastructure ◽  
Vehicle To Grid ◽  
Long Term Storage ◽  
Electricity System ◽  
Home Location ◽  
The Individual ◽  
Storage Technologies

This study describes, applies, and compares three different approaches to integrate electric vehicles (EVs) in a cost-minimising electricity system investment model and a dispatch model. The approaches include both an aggregated vehicle representation and individual driving profiles of passenger EVs. The driving patterns of 426 randomly selected vehicles in Sweden were recorded between 30 and 73 days each and used as input to the electricity system model for the individual driving profiles. The main conclusion is that an aggregated vehicle representation gives similar results as when including individual driving profiles for most scenarios modelled. However, this study also concludes that it is important to represent the heterogeneity of individual driving profiles in electricity system optimisation models when: (i) charging infrastructure is limited to only the home location in regions with a high share of solar and wind power in the electricity system, and (ii) when addressing special research issues such as impact of vehicle-to-grid (V2G) on battery health status. An aggregated vehicle representation will, if the charging infrastructure is limited to only home location, over-estimate the V2G potential resulting in a higher share (up to 10 percentage points) of variable renewable electricity generation and an under-estimation of investments in both short- and long-term storage technologies.

scholarly journals Optimal Pricing of Vehicle-to-Grid Services Using Disaggregate Demand Models

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1090
Author(s):  
Charilaos Latinopoulos ◽  
Aruna Sivakumar ◽  
John W. Polak
Keyword(s):  
Power Systems ◽  
Electric Vehicles ◽  
Power Grids ◽  
Local Distribution ◽  
Technical Problems ◽  
Vehicle To Grid ◽  
Distribution Transformers ◽  
Demand Models ◽  
Multiple Vehicles ◽  
Infrastructure Investments

The recent revolution in electric mobility is both crucial and promising in the coordinated effort to reduce global emissions and tackle climate change. However, mass electrification brings up new technical problems that need to be solved. The increasing penetration rates of electric vehicles will add an unprecedented energy load to existing power grids. The stability and the quality of power systems, especially on a local distribution level, will be compromised by multiple vehicles that are simultaneously connected to the grid. In this paper, the authors propose a choice-based pricing algorithm to indirectly control the charging and V2G activities of electric vehicles in non-residential facilities. Two metaheuristic approaches were applied to solve the optimization problem, and a comparative analysis was performed to evaluate their performance. The proposed algorithm would result in a significant revenue increase for the parking operator, and at the same time, it could alleviate the overloading of local distribution transformers and postpone heavy infrastructure investments.

Exploring the potential of rental electric vehicles for vehicle-to-grid: A data-driven approach

2021 ◽  
Vol 175 ◽  
pp. 105841
Author(s):  
Mingdong Sun ◽  
Chunfu Shao ◽  
Chengxiang Zhuge ◽  
Pinxi Wang ◽  
Xiong Yang ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Data Driven ◽  
Vehicle To Grid ◽  
Data Driven Approach
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