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: .. code-block:: ├── 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. .. csv-table:: [basic] :header: **Keyword**, **Example**, **Description** :widths: 33, 33, 33 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 .. csv-table:: [output] :header: **Keyword**, **Default**, **Description** :widths: 33, 33, 33 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 .. csv-table:: [rampup_ev] :header: **Keyword**, **Default**, **Description** :widths: 33, 33, 33 rampup, regions.csv, Link to input file for region definitions and vehicle amounts .. csv-table:: [tech_data] :header: **Keyword**, **Default**, **Description** :widths: 33, 33, 33 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 .. csv-table:: [user_data] :header: **Keyword**, **Default**, **Description** :widths: 33, 33, 33 user_groups, user_groups.csv, Link to input file for user group definitions for different charging behaviour .. csv-table:: [charging_probabilities] :header: **Keyword**, **Default**, **Description** :widths: 33, 33, 33 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 .. csv-table:: [sim_params] :header: **Keyword**, **Default/Example**, **Description** :widths: 33, 33, 33 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 ------------ .. csv-table:: [basic] :header: **Keyword**, **Default/Example**, **Description** :widths: 33, 33, 33 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, data\probability, 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 .. csv-table:: [output] :header: **Keyword**, **Default**, **Description** :widths: 33, 33, 33 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 .. csv-table:: [rampup_ev] :header: **Keyword**, **Default**, **Description** :widths: 33, 33, 33 rampup, regions.csv, Number of every vehicle type per region .. csv-table:: [tech_data] :header: **Keyword**, **Default**, **Description** :widths: 33, 33, 33 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 .. csv-table:: [user_data] :header: **Keyword**, **Default**, **Description** :widths: 33, 33, 33 user_groups, user_groups.csv, Link to input file for user group definitions for different charging behaviour .. csv-table:: [charging_probabilities] :header: **Keyword**, **Default**, **Description** :widths: 33, 33, 33 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 .. csv-table:: [sim_params] :header: **Keyword**, **Default**, **Description** :widths: 33, 33, 33 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:** .. csv-table:: charging_curve.csv :header: key,bev_mini,bev_medium,bev_luxury,phev_mini,phev_medium,phev_luxury :widths: 14,14,14,14,14,14,14 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:** .. csv-table:: charging_probability.csv :header: destination,0,3.7,11.0,22.0,50.0 :widths: 20,10,10,10,10,10 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:** .. csv-table:: charging_probability_by_usecase.csv :header: destination,22.0,50.0,150.0,250.0,350.0 :widths: 20,10,10,10,10,10 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:** .. csv-table:: energy_min.csv :header: uc,bev,phev :widths: 10,10,10 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:** .. csv-table:: fast_charging_probability.csv :header: destination,150.0,350.0 :widths: 10,10,10 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:** .. csv-table:: home_work_private.csv :header: region,LR_Klein,LR_Mitte,LR_Zentr,SR_Klein,SR_Mitte,SR_Gross,SR_Metro :widths: 20,10,10,10,10,10,10,10 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:** .. csv-table:: hpc_config.csv :header: key,values :widths: 20,10 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:** .. csv-table:: regions.csv :header: region_id,RegioStaR7,bev_mini,bev_medium,bev_luxury,phev_mini,phev_medium,phev_luxury :widths: 20,20,10,10,10,10,10,10 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:** .. csv-table:: tech_data.csv :header: type,max_charging_capacity_slow,max_charging_capacity_fast,battery_capacity,energy_consumption :widths: 20,10,10,10,10 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:** .. csv-table:: tech_data_by_probability.csv :header: type,slow_3.7,slow_11,slow_22,fast_50,fast_150,fast_350,battery_capacity,energy_consumption :widths: 20,10,10,10,10,10,10,10,10 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:** .. csv-table:: user_groups.csv :header: user_group,home_detached,home_apartment,work,urban_fast,highway_fast,retail,street :widths: 10,10,10,10,10,10,10,10 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