scholarly journals Comparing Power-System and User-Oriented Battery Electric Vehicle Charging Representation and Its Implications on Energy System Modeling

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1093 ◽  
Author(s):  
Niklas Wulff ◽  
Felix Steck ◽  
Hans Christian Gils ◽  
Carsten Hoyer-Klick ◽  
Bent van den Adel ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Power System ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
System Optimization ◽  
Energy System ◽  
Battery Electric Vehicle ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

Battery electric vehicles (BEV) provide an opportunity to balance supply and demand in future power systems with high shares of fluctuating renewable energy. Compared to other storage systems such as pumped-storage hydroelectricity, electric vehicle energy demand is highly dependent on charging and connection choices of vehicle users. We present a model framework of a utility-based stock and flow model, a utility-based microsimulation of charging decisions, and an energy system model including respective interfaces to assess how the representation of battery electric vehicle charging affects energy system optimization results. We then apply the framework to a scenario study for controlled charging of nine million electric vehicles in Germany in 2030. Assuming a respective fleet power demand of 27 TWh, we analyze the difference between power-system-based and vehicle user-based charging decisions in two respective scenarios. Our results show that taking into account vehicle users’ charging and connection decisions significantly decreases the load shifting potential of controlled charging. The analysis of marginal values of equations and variables of the optimization problem yields valuable insights on the importance of specific constraints and optimization variables. Assumptions on fleet battery availability and a detailed representation of fast charging are found to have a strong impact on wind curtailment, renewable energy feed-in, and required gas power plant flexibility. A representation of fleet connection to the grid in high temporal detail is less important. Peak load can be reduced by 5% and 3% in both scenarios, respectively. Shifted load is robust across sensitivity analyses while other model results such as curtailment are more sensitive to factors such as underlying data years. Analyzing the importance of increased BEV fleet battery availability for power systems with different weather and electricity demand characteristics should be further scrutinized.

scholarly journals Comparing Power-System- and User-Oriented Battery Electric Vehicle Charging Representation and its Implications on Energy System Modeling

2020 ◽  
Author(s):  
Niklas Wulff ◽  
Felix Steck ◽  
Hans Christian Gils ◽  
Carsten Hoyer-Klick ◽  
Bent van den Adel ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Power System ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
System Optimization ◽  
Energy System ◽  
Battery Electric Vehicle ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

Battery electric vehicles provide an opportunity to balance supply and demand in future power systems with high shares of fluctuating renewable energy. Compared to other storage systems such as pumped-storage hydroelectricity, electric vehicle energy demand is highly dependent on charging and connection choices of vehicle users. We present a model framework of a utility-based stock and flow model, a utility-based microsimulation of charging decisions, and an energy system model including respective interfaces to assess how the representation of battery electric vehicle charging affects energy system optimization results. We then apply the framework to a scenario study for controlled charging of nine million electric vehicles in Germany in 2030. Assuming a respective fleet power demand of 27 TWh, we analyze the difference between power-system-based and vehicle user-based charging decisions in two respective scenarios. Our results show that taking into account vehicle users’ charging and connection decisions significantly decreases the load shifting potential of controlled charging. The analysis of marginal values of equations and variables of the optimization problem yields valuable insights on the importance of specific constraints and optimization variables. In particular, state-of-charge assumptions and representing fast charging drive curtailment of renewable energy feed-in and required gas power plant flexibility. A detailed representation of fleet charge connection is less important. Peak load can be significantly reduced by 5% and 3% in both scenarios, respectively. Shifted load is very robust across sensitivity analyses while other model results such as curtailment are more sensitive to factors such as underlying data years. Analyzing the importance of increased BEV fleet battery availability for power systems with different weather and electricity demand characteristics should be further scrutinized.

scholarly journals Energy Management System Optimization of Drug Store Electric Vehicles Charging Station Operation

2021 ◽  
Vol 13 (11) ◽  
pp. 6163
Author(s):  
Yongyi Huang ◽  
Atsushi Yona ◽  
Hiroshi Takahashi ◽  
Ashraf Mohamed Hemeida ◽  
Paras Mandal ◽  
...  
Keyword(s):  
Power Generation ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
System Optimization ◽  
Mixed Integer ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Photovoltaic Power ◽  
Vehicle Charging ◽  
Charging Stations

Electric vehicle charging station have become an urgent need in many communities around the world, due to the increase of using electric vehicles over conventional vehicles. In addition, establishment of charging stations, and the grid impact of household photovoltaic power generation would reduce the feed-in tariff. These two factors are considered to propose setting up charging stations at convenience stores, which would enable the electric energy to be shared between locations. Charging stations could collect excess photovoltaic energy from homes and market it to electric vehicles. This article examines vehicle travel time, basic household energy demand, and the electricity consumption status of Okinawa city as a whole to model the operation of an electric vehicle charging station for a year. The entire program is optimized using MATLAB mixed integer linear programming (MILP) toolbox. The findings demonstrate that a profit could be achieved under the principle of ensuring the charging station’s stable service. Household photovoltaic power generation and electric vehicles are highly dependent on energy sharing between regions. The convenience store charging station service strategy suggested gives a solution to the future issues.

Hybrid Renewable Energy Fed Battery Electric Vehicle Charging Station

2021 ◽  
Author(s):  
R. Kannan ◽  
S. Karthikkumar ◽  
P. Suseendhar ◽  
S. Pragaspathy ◽  
B. N. Ch.V. Chakravarthi ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Electric Vehicle ◽  
Battery Electric Vehicle ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Hybrid Renewable Energy

Feasibility Study of Renewable Energy Integrated Electric Vehicle Charging Infrastructure

2016 ◽  
pp. 313-349
Author(s):  
Azhar Ul-Haq ◽  
Marium Azhar
Keyword(s):  
Renewable Energy ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Area Network ◽  
Charging Infrastructure ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations

This chapter presents a detailed study of renewable energy integrated charging infrastructure for electric vehicles (EVs) and discusses its various aspects such as siting requirements, standards of charging stations, integration of renewable energy sources for powering up charging stations and interfacing devices between charging facilities and smart grid. A smart charging station for EVs is explained along with its essential components and different charging methodologies are explained. It has been recognized that the amalgamation of electric vehicles in the transportation sector will trigger power issues due to the mobility of vehicles beyond the stretch of home area network. In this regard an information and communication technology (ICT) based architecture may support EVs management with an aim to enhance the electric vehicle charging and energy storage capabilities with the relevant considerations. An ICT based solution is capable of monitoring the state of charge (SOC) of EV batteries, health and accessible amount of energy along with the mobility of EVs.

Optimization of Smart Grid Solar Energy Application

2014 ◽  
Author(s):  
Olumide Bello ◽  
Landon Onyebueke
Keyword(s):  
Renewable Energy ◽  
Smart Grid ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Peak Load ◽  
Energy Integration ◽  
Electric Vehicle Charging ◽  
Battery Bank ◽  
Vehicle Charging

This paper presents an approach to modeling of renewable energy integration into Smart Grid for Electric Vehicle charging applications. Integration of renewable energy sources to smart grid is not only the key to smart Electric Vehicle charging but also the most efficient way to manage the distributed energy resources. It enables the ability to control, ease the peak load impacts, and protect distribution network components from being overloaded by Electric Vehicles. Thus, the electricity generation and consumption is managed in more cost effective way. The developed model is a grid connected solar-assisted Electric Vehicle charging station, with battery bank. It generates electricity using solar photovoltaic (PV) arrays to augment the electricity used to charge the electric vehicles. The battery bank stores electricity from the grid and discharges the stored energy during periods of peak charging demand. Optimization of the model was done by developing a program written in Visual Basic 2012. The computational results show the economic advantages of this model as well as the anticipated benefits of the smart grid for reduced peak loads, and increased efficiency.

scholarly journals Calculating Operational Patterns for Electric Vehicle Charging on a Real Distribution Network Based on Renewables’ Production

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2400 ◽  
Author(s):  
Stavros Lazarou ◽  
Vasiliki Vita ◽  
Christos Christodoulou ◽  
Lambros Ekonomou
Keyword(s):  
Power Systems ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
High Performance ◽  
Electric Energy ◽  
Distribution Networks ◽  
Electric Vehicle Charging ◽  
Adequate Knowledge ◽  
Real Distribution ◽  
Vehicle Charging

The connection of electric vehicles to distribution networks has been an emerging issue of paramount importance for power systems. On one hand, it provides new opportunities for climate change mitigation, if electric energy used for charging is produced from zero emission sources. On the other hand, it stresses networks that are now required to accommodate, in addition to the loads and production from distributed generation they are initially designed for, loads from electric vehicles charging. In order to achieve maximum use of the grid without substantially affecting its performance, these issues have to be addressed in a coordinated manner, which requires adequate knowledge of the system under consideration. It is advantageous that electric vehicle charging can be controlled to a certain degree. This research provides better understanding of real distribution networks’ operation, proposing specific operational points through minimizing electric vehicle charging effects. The probabilistic Monte Carlo method on high performance computers is used for the calculations.

Feasibility Study of Renewable Energy Integrated Electric Vehicle Charging Infrastructure

2020 ◽  
pp. 158-194
Author(s):  
Azhar Ul-Haq ◽  
Marium Azhar
Keyword(s):  
Renewable Energy ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Area Network ◽  
Charging Infrastructure ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations

This chapter presents a detailed study of renewable energy integrated charging infrastructure for electric vehicles (EVs) and discusses its various aspects such as siting requirements, standards of charging stations, integration of renewable energy sources for powering up charging stations and interfacing devices between charging facilities and smart grid. A smart charging station for EVs is explained along with its essential components and different charging methodologies are explained. It has been recognized that the amalgamation of electric vehicles in the transportation sector will trigger power issues due to the mobility of vehicles beyond the stretch of home area network. In this regard an information and communication technology (ICT) based architecture may support EVs management with an aim to enhance the electric vehicle charging and energy storage capabilities with the relevant considerations. An ICT based solution is capable of monitoring the state of charge (SOC) of EV batteries, health and accessible amount of energy along with the mobility of EVs.

scholarly journals Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Electricity ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 91-109
Author(s):  
Julian Wruk ◽  
Kevin Cibis ◽  
Matthias Resch ◽  
Hanne Sæle ◽  
Markus Zdrallek
Keyword(s):  
Genetic Algorithm ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Network Planning ◽  
Voltage Regulation ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
The Impact

This article outlines methods to facilitate the assessment of the impact of electric vehicle charging on distribution networks at planning stage and applies them to a case study. As network planning is becoming a more complex task, an approach to automated network planning that yields the optimal reinforcement strategy is outlined. Different reinforcement measures are weighted against each other in terms of technical feasibility and costs by applying a genetic algorithm. Traditional reinforcements as well as novel solutions including voltage regulation are considered. To account for electric vehicle charging, a method to determine the uptake in equivalent load is presented. For this, measured data of households and statistical data of electric vehicles are combined in a stochastic analysis to determine the simultaneity factors of household load including electric vehicle charging. The developed methods are applied to an exemplary case study with Norwegian low-voltage networks. Different penetration rates of electric vehicles on a development path until 2040 are considered.

scholarly journals Smart electric vehicle charging strategies for sectoral coupling in a city energy system

2021 ◽  
Vol 288 ◽  
pp. 116640
Author(s):  
Verena Heinisch ◽  
Lisa Göransson ◽  
Rasmus Erlandsson ◽  
Henrik Hodel ◽  
Filip Johnsson ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Energy System ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

scholarly journals An Optimal Control Algorithm with Reduced DC-Bus Current Fluctuation for Multiple Charging Modes of Electric Vehicle Charging Station

2021 ◽  
Vol 12 (3) ◽  
pp. 107
Author(s):  
Tao Chen ◽  
Peng Fu ◽  
Xiaojiao Chen ◽  
Sheng Dou ◽  
Liansheng Huang ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Control Algorithm ◽  
Current Fluctuation ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Three Phase ◽  
Optimization Control ◽  
Dc Bus ◽  
Vehicle Charging

This paper presents a systematic structure and a control strategy for the electric vehicle charging station. The system uses a three-phase three-level neutral point clamped (NPC) rectifier to drive multiple three-phase three-level NPC converters to provide electric energy for electric vehicles. This topology can realize the single-phase AC mode, three-phase AC mode, and DC mode by adding some switches to meet different charging requirements. In the case of multiple electric vehicles charging simultaneously, a system optimization control algorithm is adopted to minimize DC-bus current fluctuation by analyzing and reconstructing the DC-bus current in various charging modes. This algorithm uses the genetic algorithm (ga) as the core of computing and reduces the number of change parameter variables within a limited range. The DC-bus current fluctuation is still minimal. The charging station system structure and the proposed system-level optimization control algorithm can improve the DC-side current stability through model calculation and simulation verification.

Sign in / Sign up

Export Citation Format

Share Document