| 1. |
|
|
| 2. |
- Grahn, Pia, et al.
(författare)
-
A method for evaluating the impact of electric vehicle charging on transformer hotspot temperature
- 2011
-
Ingår i: 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe). - : IEEE.
-
Konferensbidrag (refereegranskat)abstract
- The expected increasing market share of electric vehicles is a response to the combination of new technological developments, governmental financial control, and an attitude shift of residents to a more environmentally friendly lifestyle. The expected capacity required for charging, imposes changes in the load to the already existing components in the electric power grid. In order to continue managing these existing assets efficiently during this load change, it is important to evaluate the impact imposed by the battery charging.
|
|
| 3. |
- Grahn, Pia, 1984-
(författare)
-
Electric Vehicle Charging Impact on Load Profile
- 2013
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- One barrier to sustainable development is considered to be greenhouse gas emissions and pollution caused by transport, why climate targets are set around the globe to reduce these emissions. Electric vehicles (EVs), may be a sustainable alternative to internal combustion engine vehicles since having EVs in the car park creates an opportunity to reduce greenhouse gas emissions. This is due to the efficiency of the electric motor. For EVs with rechargeable batteries the opportunity to reduce emissions is also dependent on the generation mix in the power system. EVs with the possibility to recharge the battery from the power grid are denoted plug-in electric vehicles (PEVs) or plug-inhybrid electric vehicles (PHEVs). Hybrid electric vehicles (HEVs), without external recharging possibility, are not studied, hence the abbreviation EV further covers PHEV and PEV.With an electricity-driven private vehicle fleet, the power system will experience an increased amount of variable electricity consumption that is dependent on the charging patterns of EVs. Depending on the penetration level of EVs and the charging patterns, EV integration creates new quantities in the overall load profile that may increase the load peaks. The charging patterns are stochastic since they are affected by the travel behavior of the driver and the charging opportunities which imply that the EV integration also will have an effect on the load variations. Increased load variation and load peaks may create a need for upgrades in the grid infrastructure to reduce the risk for losses, overloads or damaging of components. However, with well-designed incentives to the EV users the variable electricity consumption due to electric vehicle charging (EVC) may become a flexible load that can help the power system mitigate load variations and load peaks.The aim with this licentiate thesis is to investigate the impact of EVC on load profiles and load variations. The thesis reviews and categorizes EVC models in previous research. The thesis furthermore develops electric vehicle charging models to estimate the charging impact based on charging patterns induced by private car travel behavior. The models mainly consider uncontrolled charging (UCC) related to stochastic individual car travel behavior and induced charging needs for PHEVs. Moreover, the thesis comments on the potential of individual charging strategies (ICS) with flexible charging and external charging strategies (ECS).Three key factors are identified when considering the impact of EVC on load profiles and load variations. The key factors are: The charging moment, the charging need and the charging location. It is concluded that the level of details concerning the approach to model these key factors in EVC models will impact the estimations of the load profiles. This means that models taking into account a higher level of mobility details will be able to create a more realistic estimation of a future UCC behavior, enabling for more accurate estimates of the impact on load profiles and the potential of ICS and ECS.
|
|
| 4. |
- Grahn, Pia, 1984-
(författare)
-
Electric Vehicle Charging Modeling
- 2014
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- With an electrified passenger transportation fleet, carbon dioxide emissions could be reduced significantly depending on the electric power production mix. Increased electric power consumption due to electric vehicle charging demands of electric vehicle fleets may be met by increased amount of renewable power production in the electrical systems. With electric vehicle fleets in the transportation system there is a need for establishing an electric vehicle charging infrastructure that distributes this power to the electric vehicles. Depending on the amount of electric vehicles in the system and the charging patterns, electric vehicle integration creates new quantities in the overall load profile that may increase the load peaks. The electric vehicle charging patterns are stochastic since they are affected by the travel behavior of the driver and the charging opportunities which implies that an electric vehicle introduction also will affect load variations. Increased load variation and load peaks may create a need for upgrades in the grid infrastructure to reduce losses, risks for overloads or damaging of components. However, with well-designed incentives for electric vehicle users and electric vehicle charging, the electric vehicles may be used as flexible loads that can help mitigate load variations and load peaks in the power system.The aim with this doctoral thesis is to investigate and quantify the impact of electric vehicle charging on load profiles and load variations. Three key factors are identified when considering the impact of electric vehicle charging on load profiles and load variations. The key factors are: The charging moment, the charging need and the charging location. One of the conclusions in this thesis is that the level of details and the approach to model these key factors impact the estimations of the load profiles. The models that take into account a high level of mobility details will be able to create a realistic estimation of a future uncontrolled charging behavior, enabling for more accurate estimates of the impact on load profiles and the potential of individual charging strategies and external charging strategies. The thesis reviews and categorizes electric vehicle charging models in previous research, and furthermore, introduces new electric vehicle charging models to estimate the charging impact based on charging patterns induced by passenger car travel behavior. The models mainly consider EVC related to individual car travel behavior and induced charging needs for plug-in-hybrid electric vehicles. Moreover, the thesis comments on dynamic electric vehicle charging along electrified roads and also on individual charging strategies.
|
|
| 5. |
|
|
| 6. |
- Grahn, Pia, 1984-, et al.
(författare)
-
PHEV Home-Charging Model Based on Residential Activity Patterns
- 2013
-
Ingår i: IEEE Transactions on Power Systems. - 0885-8950 .- 1558-0679. ; 28:3, s. 2507-2515
-
Tidskriftsartikel (refereegranskat)abstract
- Plug-in hybrid electric vehicles (PHEVs) have received an increased interest lately since they provide an opportunity to reduce greenhouse gas emissions. Based on the PHEV introduction level in the car park, the charging behaviors in an area will induce changes in the load profiles of the power system. Hence, it becomes important to investigate what impact a given PHEV introduction level has on load profiles due to expected charging behavior of residents.
|
|
| 7. |
- Grahn, Pia, et al.
(författare)
-
PHEV Utilization Model Considering Type-of-Trip and Recharging Flexibility
- 2014
-
Ingår i: IEEE Transactions on Smart Grid. - 1949-3053 .- 1949-3061. ; 5:1, s. 139-148
-
Tidskriftsartikel (refereegranskat)abstract
- Electric vehicles (EVs) may soon enter the vehicle market in large numbers and change the overall fuel usage within the passenger transport sector. With increased variable consumption from EVs together with anticipated increased production from variable sources, due to renewable wind and solar power, also the balancing of the electric power system incur increased attention. This emphasizes the importance of developing models to estimate and investigate the stochasticity of personal car travel behavior and induced EV charging load. Several studies have been made in order to model the stochasticity of passenger car travel behavior but none have captured the charging behavior dependence of the type-of-trip conducted. This paper proposes a new model for plug-in-hybrid electric vehicle (PHEV) utilization and recharging price sensitivity, to determine charging load profiles based on driving patterns due to the type-of-trip and corresponding charging need. This approach makes it possible to relate the type-of-trip with the consumption level, the parking location, and the charging opportunity. The proposed model is applied in a case study using Swedish car travel data. The results show the charging load impact and variation due to the stochastic PHEV type-of-trip mobility, allowing quantification of the PHEV charging impact on the system.
|
|
| 8. |
|
|
| 9. |
- Grahn, Pia, et al.
(författare)
-
Plug-in-vehicle mobility and charging flexibility Markov model based on driving behavior
- 2012
-
Ingår i: 9th International Conference on the European Energy Market, EEM 12. - : IEEE. - 9781467308328
-
Konferensbidrag (refereegranskat)abstract
- Climate targets around the globe are enforcing new strategies for reducing climate impacts, which encourage automobile and electricity companies to consider an electrified vehicle market. Furthermore, the variable electricity production in the electric power system is increasing, with higher levels of wind and solar power. Due to the increased variability in the system, the need to meet fluctuations with flexible consumption is intensified. Electric vehicles with rechargeable batteries seem to become an increasingly common feature in the car fleet. Plugin vehicles (PIVs), may therefore become valuable as flexible consumers. If so, flexible PIV owners could, if they are flexible enough, increase the value of owning an electric vehicle. This paper introduces a new PIV Mobility and Charging Flexibility Markov Model, based on driving behavior for private cars. By using the new model, it is possible to simulate the potential flexibility in a future system with many PIVs. The results from a case study indicate a potential need for usage of the batteries as flexible loads to reduce the grid power fluctuations and load peaks.
|
|
| 10. |
|
|
