A Methodology for Optimization of Power Systems Demand Due to Electric Vehicle Charging Load

2012 ◽  
Vol 27 (3) ◽  
pp. 1628-1636 ◽  
Author(s):  
Peng Zhang ◽  
Kejun Qian ◽  
Chengke Zhou ◽  
Brian G. Stewart ◽  
Donald M. Hepburn
Keyword(s):  
Power Systems ◽  
Electric Vehicle ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

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.

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.

Study of the Active Power Filter for the Electric Vehicle Charging Stake

2014 ◽  
Vol 615 ◽  
pp. 48-51
Author(s):  
Chang Ping Wang ◽  
Shuo Zeng ◽  
Jie Liu
Keyword(s):  
Power Systems ◽  
Electric Vehicle ◽  
Reactive Power ◽  
Active Power Filter ◽  
Quality Standard ◽  
Active Power ◽  
Power Filter ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Ev Charging

The electric vehicle (EV) charging stake is widely used for recharging the electric car batteries. The charging stake generally adopts switching power supply technology. It will cause serious harmonic pollution to power systems and consume lots of reactive power. Therefore, this dissertation focuses on the active power filter (APF) for the EV charging stake. Firstly, the principle of the APF are briefly introduced. Secondly, the main design and the technical difficulties are illustrated in detail. The controller of the APF is based on the DSP and the model is TMS320F2812. At last, this study is simulated in Matlab and a prototype is constructed. The simulation and the experimental results prove that the APF can functions well for the electric vehicle charging stake. It has achieved the national power quality standard.

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.

An Investigation of Plug-In Electric Vehicle Charging Impact on Power Systems Scheduling and Energy Costs

2017 ◽  
Vol 32 (3) ◽  
pp. 1902-1912 ◽  
Author(s):  
Stylianos I. Vagropoulos ◽  
Georgios A. Balaskas ◽  
Anastasios G. Bakirtzis
Keyword(s):  
Power Systems ◽  
Electric Vehicle ◽  
Energy Costs ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

Decentralized Plug-in Electric Vehicle Charging Selection Algorithm in Power Systems

2012 ◽  
Vol 3 (4) ◽  
pp. 1779-1789 ◽  
Author(s):  
Chao-Kai Wen ◽  
Jung-Chieh Chen ◽  
Jen-Hao Teng ◽  
Pangan Ting
Keyword(s):  
Power Systems ◽  
Electric Vehicle ◽  
Selection Algorithm ◽  
Electric Vehicle Charging ◽  
Vehicle Charging
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