Optimization of shared autonomous electric vehicles operations with charge scheduling and vehicle-to-grid

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.

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Housing peak shaving algorithm (HPSA) with plug-in hybrid electric vehicles (PHEVs): Vehicle-to-Home (V2H) and Vehicle-to-Grid (V2G) concepts

4th International Conference on Power Engineering, Energy and Electrical Drives ◽

10.1109/powereng.2013.6635704 ◽

2013 ◽

Cited By ~ 7

Author(s):

Harun Turker ◽

Ahmad Hably ◽

Seddik Bacha

Keyword(s):

Electric Vehicles ◽

Hybrid Electric Vehicles ◽

Peak Shaving ◽

Vehicle To Grid ◽

Hybrid Electric

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Analysis of EV Cost-Based Charging Load Profiles

Proceedings ◽

10.3390/proceedings2020065002 ◽

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.

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

Energies ◽

10.3390/en14030539 ◽

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.

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

Energies ◽

10.3390/en14041090 ◽

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.

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A comparative study of on-board bidirectional chargers for electric vehicles to support vehicle-to-grid power transfer

2013 IEEE 10th International Conference on Power Electronics and Drive Systems (PEDS) ◽

10.1109/peds.2013.6527097 ◽

2013 ◽

Cited By ~ 10

Author(s):

C. Gould ◽

K. Colombage ◽

Jiabin Wang ◽

D. Stone ◽

M. Foster

Keyword(s):

Comparative Study ◽

Electric Vehicles ◽

Power Transfer ◽

Vehicle To Grid

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

Resources Conservation and Recycling ◽

10.1016/j.resconrec.2021.105841 ◽

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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A Comprehensive Emissions Model Combining Autonomous Vehicles with Park and Ride and Electric Vehicle Transportation Policies

Sustainability ◽

10.3390/su13094653 ◽

2021 ◽

Vol 13 (9) ◽

pp. 4653

Author(s):

Mohammed Obaid ◽

Arpad Torok ◽

Jairo Ortega

Keyword(s):

Electric Vehicles ◽

Autonomous Vehicles ◽

Emission Reduction ◽

Transport Sector ◽

Sustainable Transport ◽

Mode Shift ◽

Pollution Levels ◽

Park And Ride ◽

Model Combining ◽

Autonomous Electric Vehicles

Several transport policies reduce pollution levels caused by private vehicles by introducing autonomous or electric vehicles and encouraging mode shift from private to public transport through park and ride (P&R) facilities. However, combining the policies of introducing autonomous vehicles with the implementation of electric vehicles and using the P&R system could amplify the decrease of transport sector emissions. The COPERT software has been used to calculate the emissions. This article aims to study these policies and determine which combinations can better reduce pollution. The result shows that each combination of autonomous vehicles reduces pollution to different degrees. In conclusion, the shift to more sustainable transport modes through autonomous electric vehicles and P&R systems reduces pollution in the urban environment to a higher percentage. In contrast, the combination of autonomous vehicles has lower emission reduction but is easier to implement with the currently available infrastructure.

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