Simulation Settings

The simulation settings are organized in a configuration file where different parameters are set and the input data. In a directory scenarios/ there is following folder structure:

├── scenarios
       └── default
            ├── configs
            │   ├──default.cfg
            │   └──minimal.cfg
            ├── results (outputs)
            ├── charging_curve.csv
            ├── charging_probability.csv
            ├── charging_probability_by_usecase.csv
            ├── energy_min.csv
            ├── fast_charging_probability.csv
            ├── home_work_private.csv
            ├── hpc_config.csv
            ├── regions.csv
            ├── tech_data.csv
            ├── tech_data_by_probability.csv
            └── user_groups.csv

The default scenario can be seen here.

Required Parameters for a minimal simulation

As an introductory example there is a minimal configuration that offers the least amount of parameter settings.

The configuration file consists of sections. Every section has parameters or keys that have a value. Here for example the [basic] section has only two parameters: start_date and end_date. Both have values with dates that have the format YYYY-MM-DD. In the [output] section we got only booleans that signal if a certain output file should be generated.

[basic]

Keyword	Example	Description
start_date	2021-09-17	Starting date of the simulation in ISO format
end_date	2021-09-30	Ending date of the simulation in ISO format

[output]

Keyword	Default	Description
vehicle_csv	true	Saves the vehicle events with socs and energy use as csv
grid_time_series_csv	true	Saves energy use of the grid by time step as csv
plot_grid_time_series_split	false	Saves grid plots for each region
plot_grid_time_series_collective	false	Saves aggregated grid plot for the scenario
analyze	false	Saves an additional analysis csv with multiple computed values

[rampup_ev]

Keyword	Default	Description
rampup	regions.csv	Link to input file for region definitions and vehicle amounts

[tech_data]

Keyword	Default	Description
tech_data	tech_data.csv	Link to input file for technical vehicle data (for example battery capacity)
charging_curve	charging_curve.csv	Link to input file for charging curve definition
hpc_data	hpc_config.csv	Link to input file for High Power Charging parameters

[user_data]

Keyword	Default	Description
user_groups	user_groups.csv	Link to input file for user group definitions for different charging behaviour

[charging_probabilities]

Keyword	Default	Description
slow	charging_probability.csv	Link to input file for charging probabilites outside of HPC charging
fast	fast_charging_probability.csv	Link to input file for HPC charging
home_work_private	home_work_private.csv	Link to input file for availability of private charging infrastructure
energy_min	energy_min.csv	Link to input file for minimal charging requirements

[sim_params]

Keyword	Default/Example	Description
scaling	1	Simulation scaling. Example: With a scaling of 10 SimBEV would simulate only 1/10th of the given vehicles and extrapolate results
num_threads	4	Number of regions to be calculated at the same time (limited by processor cores)

All Settings

[basic]

Keyword	Default/Example	Description
start_date	2021-09-17	Starting date of the simulation
end_date	2021-09-30	Ending date of the simulation
input_type	probability	Choose what kind of input is used for driving profiles (Options: probability or profile)
input_directory	dataprobability	specify where the input data is located
eta_cp	1	Efficiency of charging points
stepsize	15	Step size of simulation (should stay at 15 min for best results)
soc_min	0.2	Minimum SoC left over at all times (not usable). Value can be between 0 and 1
charging_threshold	0.8	SoC threshold. Vehicles with higher SoC will not attempt to charge
distance_threshold_extra_urban	50	Determines if a trip is urban or extra urban by distance in kilometers
consumption_factor_highway	1.2	Extra consumption on highway trips
dc_power_threshold	50	Threshold power in kW. Anything higher is considered DC charging
threshold_retail_limitation	21	Time of day in hours until when retail charging is allowed
threshold_street_night_limitation	21	Time of day in hours where night charging methods are used (different allowed standing times)
maximum_park_time_flag	false	Toggle a maximum standing time. Higher standing times will not be allowed to charge (have to park elsewhere)
maximum_park_time	10	Time in hours. Any parking events that are shorter than this are considered for charging
street_night_charging_flag	true	Enables night charging option for street use case. This overrides the maximum park time for night events
home_night_charging_flag	false	Enables night charging option for public home use case. This overrides the maximum park time for night events
night_departure_standard_deviation	1	Standard deviation for departure. Normal distribution
night_departure_time	9	Standard departure time after night charging event. Normal distribution

[output]

Keyword	Default	Description
vehicle_csv	true	Saves the vehicle events with socs and energy use as csv
grid_time_series_csv	true	Saves energy use of the grid by time step as csv
plot_grid_time_series_split	false	Saves grid plots for each region
plot_grid_time_series_collective	false	Saves aggregated grid plot for the scenario
analyze	false	Saves an additional analysis csv with multiple computed values
timing	false	Debug option to time simulation

[rampup_ev]

Keyword	Default	Description
rampup	regions.csv	Number of every vehicle type per region

[tech_data]

Keyword	Default	Description
tech_data	tech_data.csv	Link to input file for technical vehicle data (for example battery capacity)
charging_curve	charging_curve.csv	Link to input file for charging curve definition
hpc_data	hpc_config.csv	Link to input file for High Power Charging parameters

[user_data]

Keyword	Default	Description
user_groups	user_groups.csv	Link to input file for user group definitions for different charging behaviour

[charging_probabilities]

Keyword	Default	Description
slow	charging_probability.csv	Link to input file for charging probabilites outside of HPC charging
fast	fast_charging_probability.csv	Link to input file for HPC charging
home_work_private	home_work_private.csv	Link to input file for availability of private charging infrastructure
energy_min	energy_min.csv	Link to input file for minimal charging requirements
use_case	charging_probability_by_usecase.csv	Variant to determine charging probabilities

[sim_params]

Keyword	Default	Description
scaling	1	Simulation scaling. Example: With a scaling of 10 SimBEV would simulate only 1/10th of the given vehicles and extrapolate results
num_threads	4	Number of regions to be calculated at the same time (limited by processor cores)
seed	3	RNG seed. Same seed with same input data will produce the same results
private_run_only	false	Attempts to charge all vehicles with private charging infrastructure if they have access

Input Files

charging_curve.csv

The charging intensity is described from 0.1 to 0.9 in 0.2 steps over all vehicles.

columns: key, vehicle0, vehicle1, …

example:

charging_curve.csv

key	bev_mini	bev_medium	bev_luxury	phev_mini	phev_medium	phev_luxury
0.1	0.9	0.9	0.9	0.9	0.9	0.9
0.3	0.915	0.915	0.915	0.915	0.915	0.915
0.5	0.81	0.81	0.81	0.81	0.81	0.81
0.7	0.64	0.64	0.64	0.64	0.64	0.64
0.9	0.35	0.35	0.35	0.35	0.35	0.3

charging_probability.csv

The probability of charging in the given destination by kW.

columns: destination,0,3.7,11.0,22.0,50.0

example:

charging_probability.csv

destination	0	3.7	11.0	22.0	50.0
work	0.5887	0.0411	0.1645	0.1645	0.0411
business	0.64	0.033	0.135	0.15	0.042
school	0.5887	0.0411	0.1645	0.1645	0.0411
shopping	0.5588	0.0059	0.0618	0.253	0.1206
private/ridesharing	0.655	0.0155	0.081	0.176	0.0725
leisure	0.6538	0.0154	0.0808	0.177	0.0731
home	0.4894	0.0911	0.3402	0.0715	0.0079

charging_probability_by_usecase.csv

The probability of charging by usecase in the given destination.

columns: destination,22.0,50.0,150.0,250.0,350.0

example:

charging_probability_by_usecase.csv

destination	22.0	50.0	150.0	250.0	350.0
home	1	0	0	0	0
work	1	0	0	0	0
retail	0.75	0.15	0.1	0	0
street	0.9	0.075	0.025	0	0
urban_fast	0	0.05	0.45	0.45	0.05
highway_fast	0	0	0.2	0.7

energy_min.csv

The minimum charged energy by vehicle type.

columns: uc,bev,phev

example:

energy_min.csv

uc	bev	phev
home	4	3
work	4	3
public	7	5
hpc	20	10

fast_charging_probability.csv

The fast charging probability for urban or ex-urban destinations.

columns: destination,150.0,350.0

example:

fast_charging_probability.csv

destination	150.0	350.0
urban	0.8	0.2
ex-urban	0.2	0.8

home_work_private.csv

Different values for home and work.

columns: region,LR_Klein,LR_Mitte,LR_Zentr,SR_Klein,SR_Mitte,SR_Gross,SR_Metro

example:

home_work_private.csv

region	LR_Klein	LR_Mitte	LR_Zentr	SR_Klein	SR_Mitte	SR_Gross	SR_Metro
home	0.9	0.85	0.7	0.85	0.8	0.6	0.4
work	0.7	0.7	0.7	0.7	0.7	0.7	0.7
probability_detached_home	0.9	0.8	0.7	0.6	0.5	0.4	0.3

hpc_config.csv

Configuration for high power charging.

columns: key,values

example:

hpc_config.csv

key	values
soc_end_min	0.8
soc_end_max	0.95
soc_start_threshold	0.6
park_time_max	90
distance_min	0.6
distance_max	1

regions.csv

Amount of vehicles per region and vehicle type.

columns: region_id,RegioStaR7,bev_mini,bev_medium,bev_luxury,phev_mini,phev_medium,phev_luxury

example:

regions.csv

region_id	RegioStaR7	bev_mini	bev_medium	bev_luxury	phev_mini	phev_medium	phev_luxury
LR_Klein	LR_Klein	10	5	5	5	10	1
LR_Mitte	LR_Mitte	20	30	10	2	20	10
LR_Zentr	LR_Zentr	5	5	5	5	5	5
SR_Gross	SR_Gross	5	5	5	10	5	2
SR_Klein	SR_Klein	1	1	5	10	0	10
SR_Metro	SR_Metro	10	30	20	30	20	20
SR_Mitte	SR_Mitte	20	5	30	10	20	15

tech_data.csv

Technical data for every vehicle type in terms charging, capacity and consumption.

columns: type,max_charging_capacity_slow,max_charging_capacity_fast,battery_capacity,energy_consumption

example:

tech_data.csv

type	max_charging_capacity_slow	max_charging_capacity_fast	battery_capacity	energy_consumption
bev_mini	11	50	60	0.1397
bev_medium	22	50	90	0.1746
bev_luxury	50	150	110	0.2096
phev_mini	3.7	0	14	0.1425
phev_medium	11	0	20	0.1782
phev_luxury	11	0	30	0.2138

tech_data_by_probability.csv

Technical probability data for every vehicle type in terms charging, capacity and consumption.

columns: type,slow_3.7,slow_11,slow_22,fast_50,fast_150,fast_350,battery_capacity,energy_consumption

example:

tech_data_by_probability.csv

type	slow_3.7	slow_11	slow_22	fast_50	fast_150	fast_350	battery_capacity	energy_consumption
bev_mini	0.05	0.80	0.15	0.30	0.65	0.05	60	0.1397
bev_medium	0	0.7	0.3	0.3	0.6	0.1	90	0.1746
bev_luxury	0	0.8	0.2	0	0.85	0.15	110	0.2096
phev_mini	0.9	0.1	0	1	0	0	14	0.1425
phev_medium	0.5	0.2	0.3	1	0	0	20	0.1782
phev_luxury	0.75	0.25	0	1	0	0	30	0.2138

user_groups.csv

Data on user groups in different areas.

columns: user_group,home_detached,home_apartment,work,urban_fast,highway_fast,retail,street

example:

user_groups.csv

user_group	home_detached	home_apartment	work	urban_fast	highway_fast	retail	street
0	0.85	0.85	0.6	0.2	0.25	0.2	0.1
1	0.95	0.95	0	0.2	0.3	0.2	0.1
2	0	0	0.95	0.3	0.55	0.4	0.4
3	0	0	0	0.4	0.6	0.55	0.7