Scipediacontent: Scipediacontent moved page Draft Content 429795733 to Leemput 2015a

2021-01-26T14:43:38Z

Scipediacontent moved page Draft Content 429795733 to Leemput 2015a

Scipediacontent: Created page with " == Abstract == The number of plug-in electric vehicles (PEVs) on the road is growing significantly, which allows to reduce the consumption of greenhouse gas emitting fossil..."

2021-01-26T14:43:32Z

Created page with " == Abstract == The number of plug-in electric vehicles (PEVs) on the road is growing significantly, which allows to reduce the consumption of greenhouse gas emitting fossil..."

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== Abstract ==

The number of plug-in electric vehicles (PEVs) on the road is growing significantly, which allows to reduce the consumption of greenhouse gas emitting fossil fuels, such as gasoline and diesel. This is due to the increased primary energy efficiency of electrically powered vehicles compared to conventional vehicles on the one hand, and the primary fuel flexibility for electricity generation on the other hand. The absence of tailpipe emissions reduces the local concentrations of harmful pollutants, which is benefits human health. PEVs are able to charge at every location that offers a suitable grid connection opportunity, e.g., at home and the workplace. The typical long standstill times at these locations and the low average daily driven distances allow low-power charging to fulfill the majority of the mobility needs, thereby keeping the charging infrastructure investments low. As the number of PEVs on the road increases, the grid impact of PEV charging is observed more widely, e.g., altered grid load profiles, increased peak power, and increased voltage magnitude deviations. Therefore, an extensive amount of research is conducted on coordinated charging strategies that have the objective to mitigate the grid impact of PEV charging. Typically, large-scale coordination mechanisms are being investigated, which require a sufficiently high large-scale PEV penetration rate to be effective. However, due to the clustering of PEV users, high local concentrations may occur prior to a high widespread PEV penetration. Therefore, certain distribution grids will already be impacted in the near-term future. More specifically, the residential low voltage (LV) grid impact may be challenging, due to the simultaneity between PEV charging and residential electricity consumption. This dissertation investigates several local PEV charging strategies that have the objective to mitigate the distribution grid impact with a minimal amount of external input. Two active power control strategies for PEV charging are assessed separately and in combination: voltage-dependent charging and standstill time-based charging. The former strategy does not need require any input, as the voltage magnitude is measured anyway within the onboard charger. The latter strategy only requires the next departure time, so that the charging power rating can be reduced as much as possible, while still being fully charged for the next trip. Besides the abovementioned active power control strategies, reactive power control is also investigated, i.e., reactive power current injections during PEV charging. Certain PEV charger topologies allow for the injection of reactive power flows into the grid, so this capability could be enabled. The advantage compared to the active power control strategies is that, given an appropriate sizing of the PEV charger, this grid-supportive measure does not impact the user comfort, because the active power flow is not altered. Reactive current injection does not require any external inputs, because it is merely a power factor set point of the onboard PEV charger. Finally, the distribution grid impact and sizing requirements of fast charging infrastructure is assessed. Opposed to plug-in hybrid electric vehicles (PHEVs), all of the required propulsion energy for battery electric vehicles (BEVs) must be delivered by the onboard battery. Therefore, fast charging is indispensable for long-distance driving, so that recharging does not take excessively long. Because slow and fast charging are complementary charging options, different slow charging strategies are taken into account when the fast charge requirements are assessed. Furthermore, different representative LV grid topologies are taken into account, as well as the medium voltage (MV) grid topology to which the different LV grids and the fast charging infrastructure are connected. The proposed local active and reactive power control strategies allow to substantially mitigate the distribution grid impact of PEV charging, with limited adaptations compared to their current implementation. The active power control strategies could be implemented on all of the currently used onboard PEV chargers. The reactive power control strategies can be implemented on onboard PEV chargers with a full-bridge IGBT rectifier topologies, as used for several PEVs. The distribution grid impact of the slow charging control strategies is more significant than the presence of fast charging infrastructure. Therefore, it the limited additional distribution grid impact of fast charging infrastructure can even be compensated for by implementing the proposed control strategies for slow charging. Abstract i Samenvatting iii List of abbreviations v List of symbols vii Contents xi List of figures xv List of tables xix 1. Introduction 1 1.1 Context and motivation 1 1.2 Scope and objectives 2 1.3 Outline 3 1.4 Contributions 6 2. Plug-in electric vehicle charging 7 2.1 Electric vehicle types 7 2.1.1 Battery electric vehicles 7 2.1.2 (Plug-in) hybrid electric vehicles 8 2.2 Plug-in electric vehicle batteries 11 2.2.1 Cell types 12 2.2.2 Battery pack 13 2.2.3 Battery charger 15 2.3 Charging infrastructure 17 2.3.1 Charging cases 17 2.3.2 Charging modes 18 2.3.3 Connection types 20 2.3.4 Grid connection 22 2.4 Distribution grid 23 2.4.1 LV grid layout 23 2.4.2 MV grid layout 25 2.4.3 Distribution grid constraints 26 2.5 Conclusions on PEV charging 30 3. Vehicle and fleet modeling 31 3.1 Mobility behavior 31 3.1.1 Mobility modeling 31 3.1.2 Fleet mobility behavior 32 3.2 Fleet segmentation 35 3.3 Energy efficiency modeling 38 3.3.1 Calculations 38 3.3.2 General parameters 41 3.3.3 Driving cycle 42 3.3.4 Results 44 3.3.5 Sensitivity analysis 45 3.4 Fleet power consumption 48 3.4.1 Daily power consumption 48 3.4.2 Grid impact parameters 49 3.4.3 Results 51 3.5 Conclusions 62 4. Coordinated charging 65 4.1 Background 65 4.1.1 Impact and scenario analysis 66 4.1.2 Grid planning and benchmarking 66 4.1.3 Coordination systems 67 4.2 Layers 67 4.2.1 Planning layers 69 4.2.2 Implementation layer 71 4.2.3 Operational layers 72 4.3 Objectives 73 4.3.1 Technical objectives 73 4.3.2 Economic objectives 73 4.3.3 Coupled techno economic objectives 74 4.4 Methods 75 4.4.1 Centralized methods 75 4.4.2 Distributed methods 75 4.4.3 Hierarchical methods 76 4.5 Scale of coordination 76 4.6 Correlation mapping 77 4.6.1 Research category vs. coordination objective 77 4.6.2 Research category vs. scale of coordination 78 4.6.3 Scale of coordination vs. coordination objective 79 4.6.4 Research category vs. coordination method 79 4.6.5 Scale of coordination vs. coordination method 80 4.6.6 Coordination method vs. coordination objective 81 4.7 Conclusion 81 5. Active power control 83 5.1 Background 83 5.2 Materials and methods 86 5.2.1 Distribution grid data 86 5.2.2 Residential load and generation 87 5.2.3 PEV charging load 88 5.2.4 Charging cases 88 5.2.5 Simulation approach 91 5.3 Results and discussion 91 5.3.1 Charging behavior 91 5.3.2 Voltage droop charging behavior 93 5.3.3 Power profile 94 5.3.4 Voltage magnitude profile 96 5.3.5 Voltage unbalance factor 97 5.4 Conclusions 97 6. Reactive power control 99 6.1 Background 99 6.2 Materials and methods 101 6.2.1 Distribution grid data 101 6.2.2 Residential load and generation 102 6.2.3 PEV charging behavior 104 6.2.4 Simulation approach 106 6.3 Results and discussion 107 6.3.1 User impact 107 6.3.2 Charging behavior 108 6.3.3 Grid voltages 111 6.3.4 Transformer peak load 114 6.3.5 Grid losses 115 6.4 Grid topology sensitivity 116 6.5 Conclusions 120 7. Fast charging 123 7.1 Background 123 7.1.1 Complementarity of slow and fast charging 123 7.1.2 Research on fast charging infrastructure 124 7.1.3 Scope 125 7.2 Materials and methods 125 7.2.1 Distribution grid data 125 7.2.2 Residential load and generation 128 7.2.3 PEV charging behavior 128 7.2.4 Simulation approach 130 7.3 Results and discussion 131 7.3.1 User impact 131 7.3.2 Charging behavior 132 7.3.3 PEV hosting capacity 135 7.3.4 Fast charging requirements 137 7.3.5 Peak load 138 7.4 Conclusions 139 8. Summary, conclusions, and future work 141 8.1 Summary & conclusions 141 8.2 Future work 143 Appendix A North-American grid layout 147 Appendix B Availability analysis 149 B.1 Flemish travel behavior data 149 B.2 Commute trips 152 B.3 Other trips 154 Appendix C Fast charging scenario 159 Bibliography 161 Curriculum Vitae 179 List of publications 181 nrpages: 183 status: published

== Original document ==

The different versions of the original document can be found in:

* [https://lirias.kuleuven.be/handle/123456789/511457 https://lirias.kuleuven.be/handle/123456789/511457]

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Leemput 2015a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 429795733 to Leemput 2015a

Scipediacontent: Created page with " == Abstract == The number of plug-in electric vehicles (PEVs) on the road is growing significantly, which allows to reduce the consumption of greenhouse gas emitting fossil..."