Title Page
ABSTRACT
Contents
Chapter 1. Introduction 13
1.1. Research Background 13
1.2. Related Research Trends 14
1.3. Dissertation Structure 17
Chapter 2. Estimating the Required Density of EV Charging Stations (ERDEC) Model 19
2.1. Analytical Planning Model 19
2.1.1. Scheme of ERDEC Model 19
2.1.2. Mathematical Formulation 20
2.1.3. Cost Model of ERDEC 25
2.1.4. The Objective Function of ERDEC 28
2.2. Sensitive Study based on ERDEC Model 29
2.2.1. The Effect of Regional Parameters 32
2.2.2. The Effect of Technological Parameters 36
2.2.3. The Effect of Coefficient Factors 38
2.3. Case Study : Application to the Real World 39
Chapter 3. Optimal Deployment of EV Chargers (ODEC) Model 43
3.1. Detailed Deployment Model 43
3.1.1. Scheme of ODEC Model 43
3.1.2. Framework of ODEC Model 43
3.2. Simulation of ODEC Model 45
3.2.1. Data Description 45
3.2.2. Simulation Rule 47
3.2.3. Identifying Charging Points 47
3.2.4. Finding the Closest Charging Stations 49
3.3. Uncapacitated Problem Simulation 52
3.3.1. Finding the peak demand 52
3.3.2. Result : Deployment Map based on Peak Demand 55
3.4. Capacitated Problem Simulation 56
3.4.1. The Cost Model of ODEC 56
3.4.2. The Method of Using Evolution Algorithm 58
3.4.3. Result : Optimal Deployment Map 59
Chapter 4. Integrated Model Development 63
4.1. The Objective of Integrated Model 63
4.2. Suitable Cell Size of ERDEC 63
4.3. Correction Factor for ERDEC 65
4.3.1. Difference between the Expected Trip Length and Real Trip Length 65
4.3.2. Setting Correction Factor 68
4.4. Combining Two Models as an Integrated Model 72
4.4.1. Proposing Candidate Locations of Charging Stations by ERDEC Model 72
4.4.2. Optimal Distribution by ODEC Model 75
4.4.3. Result 80
Chapter 5. EV Taxi Driving Pattern caused by Charging Station 84
5.1. Objective 84
5.2. General Taxi Driving Pattern in Urban Area 84
5.2.1. Trip Length in Cell 84
5.2.2. Origin-Destination Density Pattern 87
5.2.3. Origin-destination direction pattern 89
5.3. EV Driving Pattern caused by Constraints of Charging Station 91
5.3.1. Trip Length in Cell 92
5.3.2. Origin-Destination Density Pattern 95
5.3.3. Origin-Destination Direction Pattern 96
5.4. Result : Comparing Patterns between General Taxi and EV Taxi 97
5.4.1. Trip Length in Cell 97
5.4.2. Origin-Destination Direction Pattern 102
Chapter 6. Conclusions 108
6.1. Summary of dissertation 108
6.2. Contribution of Dissertation 110
6.3. Limitation and future Study 111
References 113
요약문 118
Curriculum Vitae 120
Table 1. Literature review summary 17
Table 2. Experimental data of real EV taxi 30
Table 3. Compilation of information on EV driving and charging 30
Table 4. Parameters as the baseline of model 31
Table 5. Coefficient factors of EV taxi 38
Table 6. Preferences of parameters 40
Table 7. Taxi GPS data descrpition 45
Table 8. Input data for agent based simulation 47
Table 9. Charging demand for each time period (1 hour) 53
Table 10. Coefficient factors of EV taxi 58
Table 11. the preference of EA parameters 58
Table 12. Simulation result 61
Table 13. EA parameters for an integrated model 80
Table 14. Simulation result 82
Table 15. Basic statistics of trip lengths 98
Table 16. Summary of the cells over 90 degree difference 106
Figure 1. Research motivation 14
Figure 2. Research frame 18
Figure 3. ERDEC scheme 20
Figure 4. Vehicles' movement 20
Figure 5. Additional trip for charging 22
Figure 6. Delay time 24
Figure 7. Plot of ERDEC model (baseline) 32
Figure 8. The variation of L 33
Figure 9. The variation of Nveh(이미지참조) 34
Figure 10. The variation of p 35
Figure 11. The variation of k 36
Figure 12. The variation of Tf_ch(이미지참조) 37
Figure 13. The variation of lEVdis(이미지참조) 37
Figure 14. Comparison between passenger EV and EV taxi 38
Figure 15. Daejeon area divided by 1km 1km cells 39
Figure 16. Nveh in each cell(이미지참조) 40
Figure 17. The result map of the optimal density 41
Figure 18. The Scheme of ODEC Model 43
Figure 19. The framework of ODEC Model 44
Figure 20. The battery profile 46
Figure 21. Candidate charging stations 46
Figure 22. Drawing trajectory 48
Figure 23. Charging points per 1 day 49
Figure 24. Matching to the nearest charging station 50
Figure 25. Charging demand at each charging station 50
Figure 26. Charging demand map 51
Figure 27. Charging demand pattern of three days 52
Figure 28. Box plot of three days charging demand 52
Figure 29. Peak demand 54
Figure 30. Comparing peak demand pattern (3days) 54
Figure 31. Box plot of comparing peak demand pattern (3days) 55
Figure 32. Deployment map according to peak demand 56
Figure 33. Solution progress based on EA 59
Figure 34. Optimal number of chargers at each station 60
Figure 35. Optimal deployment map 60
Figure 36. Comparing the simulation results 62
Figure 37. Research frame of integrated model 63
Figure 38. Results according to cell(L) size 64
Figure 39. Total cost and the number of charging stations according to L 65
Figure 40. Limitation of assumption 66
Figure 41. Difference between expected trip length and real trip length 66
Figure 42. Comparing the expected trip lengh with the real trip length 67
Figure 43. Difference index chart 68
Figure 44. Difference index map 68
Figure 45. Correction factor map 70
Figure 46. Correction factor maps of 3 days 70
Figure 47. Comparing correction factors of 3 days 71
Figure 48. Box plot of comparing correction factors 71
Figure 49. Positive&negative pattern of 3 days correction factors 72
Figure 50. Corrected number of passing vehicles 73
Figure 51. Optimal density map based on corrected number of passing vechicles 74
Figure 52. Candidate locations of charging stations 75
Figure 53. Matching to the closest charging station 76
Figure 54. Day demand 77
Figure 55. Day demand map 77
Figure 56. Peak demand 78
Figure 57. Peak demand map 78
Figure 58. Solution progress 80
Figure 59. Optimal number of chargers 81
Figure 60. Optimal deployment map 81
Figure 61. Comparing simulation visual results 82
Figure 62. General taxis trajectories map 85
Figure 63. Sum of trip lengths on each cell 86
Figure 64. Individual taxis driving patterns for one month 86
Figure 65. OD density map [1hour, 08:00~09:00, Sept. 11, 2013] 87
Figure 66. OD density map [AM, 00:00~12:00, Sept. 11, 2013] 87
Figure 67. OD density map [PM, 12:00~24:00, Sept. 11, 2013] 88
Figure 68. OD density map [24hours, 00:00~24:00, Sept. 11, 2013] 88
Figure 69. The number of OD on each cell [24hours, 00:00~24:00, Sept. 11, 2013] 89
Figure 70. The bearing angle (θ) 89
Figure 71. The bearing angles map of OD 90
Figure 72. Historam of bearing angles 90
Figure 73. Average angles of OD 91
Figure 74. The location of charging stations 92
Figure 75. EV taxi A : trajectory and trip lengths map 93
Figure 76. EV taxi B : trajectory and trip lengths map 93
Figure 77. EV taxi C : trajectory and trip lengths map 94
Figure 78. The sum of 3 EV taxis trip length on each cell 94
Figure 79. EV taxi A : OD density map 95
Figure 80. EV taxi B : OD density map 95
Figure 81. EV taxi C : OD density map 96
Figure 82. EV taxi A : OD bearing angles and average bearing angles on each cell 96
Figure 83. EV taxi B : OD bearing angles and average bearing angles on each cell 97
Figure 84. EV taxi C : OD bearing angles and average bearing angles on each cell 97
Figure 85. All EV taxis : trip length difference map 99
Figure 86. EV taxi A : trip length difference map 100
Figure 87. EV taxi B : trip length difference map 100
Figure 88. EV taxi C : trip length difference map 101
Figure 89. The cells with greater difference than average trip length of general taxis 101
Figure 90. EV taxis : The upper 80% trip length cells 102
Figure 91. General taxis : The upper 80% trip length cells 102
Figure 92. EV taxi A : bearing difference map 103
Figure 93. EV taxi B : bearing difference map 104
Figure 94. EV taxi C : bearing difference map 104
Figure 95. EV taxi A : Cumulative number of cells over 90 degree 105
Figure 96. EV taxi B : Cumulative number of cells over 90 degree 105
Figure 97. EV taxi C : Cumulative number of cells over 90 degree difference 106
Figure 98. Result maps of models 109