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 Modeling the Future California Electricity Grid and Renewable Energy Integration with Electric Vehicles

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5277 ◽  
Author(s):  
Florian van Triel ◽  
Timothy E. Lipman
Keyword(s):  
Electric Vehicles ◽  
Capital Investment ◽  
Cost Model ◽  
Cost Effective ◽  
Energy Integration ◽  
Electricity Grid ◽  
Charging Infrastructure ◽  
Simulation Tools ◽  
Storage Technologies ◽  
Charging Demand

This study focuses on determining the impacts and potential value of unmanaged and managed uni-directional and bi-directional charging of plug-in electric vehicles (PEVs) to integrate intermittent renewable resources in California in the year 2030. The research methodology incorporates the utilization of multiple simulation tools including V2G-SIM, SWITCH, and GridSim. SWITCH is used to predict a cost-effective generation portfolio to meet the renewable electricity goals of 60% in California by 2030. PEV charging demand is predicted by incorporating mobility behavior studies and assumptions charging infrastructure and vehicle technology improvements. Finally, the production cost model GridSim is used to quantify the impacts of managed and unmanaged vehicle-charging demand to electricity grid operations. The temporal optimization of charging sessions shows that PEVs can mitigate renewable oversupply and ramping needs substantially. The results show that 3.3 million PEVs can mitigate over-generation by ~4 terawatt hours in California—potentially saving the state up to about USD 20 billion of capital investment costs in stationary storage technologies.

scholarly journals Electric Vehicles as Flexibility Management Strategy for the Electricity System—A Comparison between Different Regions of Europe

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2597 ◽  
Author(s):  
Maria Taljegard ◽  
Lisa Göransson ◽  
Mikael Odenberger ◽  
Filip Johnsson
Keyword(s):  
Wind Power ◽  
Electric Vehicles ◽  
Management Strategy ◽  
Road Transport ◽  
Investment Model ◽  
Transport Sector ◽  
Renewable Electricity ◽  
Technical Limitation ◽  
Electricity System ◽  
The Uk

This study considers whether electric vehicles (EVs) can be exploited as a flexibility management strategy to stimulate investments in and operation of renewable electricity under stringent CO2 constraints in four regions with different conditions for renewable electricity (Sweden, Germany, the UK, and Spain). The study applies a cost-minimisation investment model and an electricity dispatch model of the European electricity system, assuming three types of charging strategies for EVs. The results show that vehicle-to-grid (V2G), i.e., the possibility to discharging the EV batteries back to grid, facilitates an increase in investments and generation from solar photovoltaics (PVs) compare to the scenario without EVs, in all regions except Sweden. Without the possibility to store electricity in EV batteries across different days, which is a technical limitation of this type of model, EVs increase the share of wind power by only a few percentage points in Sweden, even if Sweden is a region with good conditions for wind power. Full electrification of the road transport sector, including also dynamic power transfer for trucks and buses, would decrease the need for investments in peak power in all four regions by at least 50%, as compared to a scenario without EVs or with uncontrolled charging of EVs, provided that an optimal charging strategy and V2G are implemented for the passenger vehicles.

Electrifying Transportation

Greenovation ◽  
2020 ◽  
pp. 94-121
Author(s):  
Joan Fitzgerald
Keyword(s):  
United States ◽  
Electric Vehicles ◽  
The United States ◽  
Grid Integration ◽  
Charging Infrastructure ◽  
Vehicle To Grid ◽  
European Cities ◽  
Renewable Power ◽  
Delivery Vehicles ◽  
Charging Stations

Cities have a key role in accelerating the adoption of electric vehicles, particularly in building charging infrastructure. This chapter examines the efforts of five leading cities—three European cities and two in the United States—each with a different set of challenges. It shows that they have different strategies for addressing regulatory and planning issues that determine what types of charging stations can be placed where and how to charge for electricity. Some cities are electrifying their bus fleets and supporting the transition of taxi fleets and delivery vehicles to electric. Several are examining ways to charge using renewable power. And a few cities are pursuing vehicle-to-grid integration—two-way interaction in which cars can push power back into the grid during periods of peak demand. The electrified transportation experiments in these five cities have met largely with success, and their innovations are already spreading to others.

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.

Blockchain technology based decentralized energy management in multi-microgrids including electric vehicles

2021 ◽  
pp. 1-12
Author(s):  
Pulimamidi Meghana ◽  
Chandrasekhar Yammani ◽  
Surender Reddy Salkuti
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Vehicle To Grid ◽  
Blockchain Technology ◽  
Price Auction ◽  
Battery Degradation ◽  
Second Price Auction ◽  
Decentralized Energy ◽  
The Individual ◽  
Contribution Index

This paper proposes an energy scheduling mechanism among multiple microgrids (MGs) and also within the individual MGs. In this paper, electric vehicle (EV) energy scheduling is also considered and is integrated in the operation of the microgrid (MG). With the advancements in the battery technologies of EVs, the significance of Vehicle-to-Grid (V2G) is increasing tremendously. So, designing the strategies for energy management of electric vehicles (EVs) is of paramount importance. The battery degradation cost of an EV is also taken into account. Vickrey second price auction is used for truthful bidding. To enhance the security and trust, blockchain technology can be incorporated. The market is shifted to decentralized state by using blockchain. To encourage the MGs to generate more, contribution index is allotted to each prosumer of a MG and to the MGs as a whole, depending on which priority is given during auction. The system was simulated using IEEE 118 bus feeder which consists of 5 MGs, which in turn contain EVs and prosumers.

scholarly journals Heuristic Optimization of Overloading Due to Electric Vehicles in a Low Voltage Grid

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6069
Author(s):  
Sajjad Haider ◽  
Peter Schegner
Keyword(s):  
Electric Vehicles ◽  
Low Voltage ◽  
Optimization Methods ◽  
Monte Carlo Analysis ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Worst Case ◽  
Voltage Drops ◽  
The Individual ◽  
Nodal Voltage

It is important to understand the effect of increasing electric vehicles (EV) penetrations on the existing electricity transmission infrastructure and to find ways to mitigate it. While, the easiest solution is to opt for equipment upgrades, the potential for reducing overloading, in terms of voltage drops, and line loading by way of optimization of the locations at which EVs can charge, is significant. To investigate this, a heuristic optimization approach is proposed to optimize EV charging locations within one feeder, while minimizing nodal voltage drops, cable loading and overall cable losses. The optimization approach is compared to typical unoptimized results of a monte-carlo analysis. The results show a reduction in peak line loading in a typical benchmark 0.4 kV by up to 10%. Further results show an increase in voltage available at different nodes by up to 7 V in the worst case and 1.5 V on average. Optimization for a reduction in transmission losses shows insignificant savings for subsequent simulation. These optimization methods may allow for the introduction of spatial pricing across multiple nodes within a low voltage network, to allow for an electricity price for EVs independent of temporal pricing models already in place, to reflect the individual impact of EVs charging at different nodes across the network.

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.

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