Input

To structure the input dataset, the jointly modeled systems are grouped into separated categories according to the following image.

The input data can be changed in the according interfaces. The configuration of the technical setup of the simulation procedure can be changed in the project configuration. The project configurations are equal for all scenarios belonging to the same project except the simulation start and end date. The simulation start and end date is used from the scenario configuration.

Input file overview

Maon uses the following input files by default formatted in comma-separated values (CSV):

Files of type timeseries contain hourly value series for each bidding zone. Files of type component specify individual components by their names and characteristics. The from-until-timeseries type defines segmented timeseries based on specified start and end intervals.

Key words

The header of input files must be defined in the first row with specifiers. Other rows and columns can be set in any order. Timeseries have the key word hour and bidding zone names as a header. Component and combined files include header specifiers that can be labeled with following keywords.

Entries for _opt can be left out completely or can be given only for selected components (others blank). If such parameters are not set, default values are used (data enrichment with best guess, see enrichment). Header specifiers labeled with the keyword _aux are ignored by the simulation core, but used by the data storing during processings and visualizations like decommission year, component validity or geographical coordinates. Header specifiers labeled with the keyword _meta are ignored, but saved for additional information like uniquely assigned Energy Identification Code (EIC) or voltage level (see metadata). Units in brackets inside header specifiers cannot be changed or omitted.

Time stamps can be given either as hour numbers (1, 2, 3, …) or with from and until time stamps (DDMMYY@HH:MM). From and until time stamps can cover multiple time intervals so that corresponding definitions can be summarized into one entry. Hour numbers relate to the hour number in the time range of the according scenario. If for example the scenario from time stamp lies at 010118@00:00, the hour number 1 relates to the time interval between 010118@00:00 and 010118@01:00, the hour number 2 relates to the time interval between 010118@01:00 and 010118@02:00 and so on.

All input file names can be customized in the project configuration.

Configurations

The configuration comprises parameters in the file 00_configurations.txt (key-value-file). In this configuration file the column delimiter is =. By leaving configuration parameters default values are used. Configurations can be exported and imported via the text file or edited in the project configuration front-end. The parameters define loaded files, preprocessings, simulation procedures, postprocessings and written out files. Configuration parameters customize folder names, file names, descriptor names, default assumptions, checks, procedure steps, optimizer configurations, model configurations, model variations, procedure variations and read-out configurations. Every configuration parameter and the total configuration combination are checked for validity and consistency. In case of missing validity or consistency the user receives a problem description and a solution proposal in the data check. Default values, possible values, the current setup and explanations for every parameter can be looked up at the project configuration in the front-end.

The minimum configuration file includes the simulation start time stamp and the simulation end time stamp. Maon writes both parameters automatically in the file based on the selected scenario. For example:

procedure_interval_start = 010118@00:00
procedure_interval_end = 311218@24:00

If there were no start and end time stamps set manually during the scenario creation, then the application sets such dates automatically according to the scenario year. The used configuration parameters are written out in the subfolder output/reference. In addition, the complete considered input data model is written out. This reference dataset includes input parameters provided by the user and it includes all enriched input parameters provided by Maon. This documentation refers to default configurations, names and formats. Apart from the the overall configuration, build-in aggregations can be enabled in 90_grid_bidding_zones.csv. Then components are aggregated during the preprocessing (see preprocessing).

Input taxonomy

In this section the taxonomy of every input file is explained. The taxonomy includes the definition for each single statement.

Spot demands

10_demands_spot.csv defines the price-inelastic spot market demand per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. For example:

FCR demands

11_demands_fcr.csv defines the price-inelastic symmetric Frequency Containment Reserve (FCR) market demand per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. It has the same format as the spot market demand. It defines the spot market demand as a constant value during the hour per bidding zone.

Positive aFRR demands

12_demands_afrr_positive.csv defines the price-inelastic positive automatic Frequency Restoration Reserve (aFRR) market demand per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. It has the same format as the spot market demand.

Negative aFRR demands

13_demands_afrr_negative.csv defines the price-inelastic negative automatic Frequency Restoration Reserve (aFRR) market demand per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. It has the same format as the spot market demand.

Positive mFRR demands

14_demands_mfrr_positive.csv defines the price-inelastic positive manual Frequency Restoration Reserve (mFRR) market demand per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. It has the same format as the spot market demand.

Negative mFRR demands

15_demands_mfrr_negative.csv defines the price-inelastic negative manual Frequency Restoration Reserve (mFRR) market demand per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. It has the same format as the spot market demand.

DSR consumers

20_dsr_consumers.csv defines the price-dependent demand-side response consumers with the following schema:

The parameter tech(EC/EH/EL/EV/IC/OT) sets the technology to one of the following categories used for enrichment of missing optional values and grouping components in the output.

Additionally, 20_dsr_consumers.csv can define the following optional spot parameters:

The exogenous initial load (before DSR load-shift or load-adjustment) is defined in the spot demand file 10_demands_spot.csv.

During the time frame between time_stamp_from and time_stamp_until the consumer in bidding_zone can increase the load up to p_max_up_opt(MW) and decrease the load up to p_max_down_opt(MW) via load-shifts in time up to max_shift_opt(h). The parameter efficiency_shift_opt(%) sets the efficiency for a load-shift into this time frame resulting in a load-increase. The parameter cost_opt(EUR/MWh) sets the work cost (also called activation price).

Additionally, 20_dsr_consumers.csv can define the following optional reserve parameters:

p_max_fcr_opt(MW) defines the maximum symmetric Frequency Containment Reserve (FCR) provision of the flexible demand component. p_max_afrr_pos_opt(MW) and p_max_afrr_neg_opt(MW) set the maximum positive and negative automatic Frequency Restoration Reserve (aFRR) provision. p_max_mfrr_pos_opt(MW) and p_max_mfrr_neg_opt(MW) set the maximum positive and negative manual Frequency Restoration Reserve (mFRR) provision. Reserve product signs are in line with the generator reference-arrow system, so positive reserve provisions require downward load potentials and negative reserve provisions require upward load potentials. Due to the flexible reserve activation, reserve provision potentials cannot be assigned to load-shifts, but to load-increase, load-decrease and twoway load adjustments. To simulate more than one reserve per direction (e.g., more than one positive and one negative quality) or to simulate the FCR, the detailed reserve module must be activated in the configuration via parameter demand_reserves_high_resolution.

DSR potentials

21_dsr_potentials.csv defines time-depebndend demand-side response potentials with the following schema:

Additionally, for every rime range, the following optional potentials can be set.

DSR mustruns, outages and revisions

22_dsr_mustruns_outages_revisions.csv defines optional exogenous mustruns, outages, and revisions of DSR consumers with the following schema:

Additionally, 22_dsr_mustruns_outages_revisions.csv can specify for every event following optional parameters:

For the time frame between time_stamp_from and time_stamp_until the maximum load-increase is restricted to the valus p_max_load_increase_opt(MW) and the maximum load-decrease power to p_max_load_decrease_opt(MW).

DSR work restrictions

23_dsr_restrictions_work.csv defines the time-dependent work restrictions of demand-side response consumers with following schema:

Additionally, 23_dsr_restrictions_work.csv can specify following optional parameters:

If a work restriction specifies minimum and maximum load-increase values, the linked DSR consumers have to dispatch within the defined work range.

DSR availabilities

24_dsr_availabilities.csv defines the availabilities of demand-side response consumers with following schema:

The outage and revision drawing is carried out for every outage and revision cluster defined by bidding_zone and tech(EC/EH/EL/EV/IC/OT) in the system as well as time_stamp_from and time_stamp_until in time. availability(%) defines the average work availability of this cluster.

Additionally, for every outage and revision cluster, the following optional drawing parameters can be set.

The parameters event_duration_expectation_opt(h) and event_duration_deviation_opt(h) define the mean and standard deviation of the normal distribution for outage or revision event durations specified in the file line.

Battery storages

30_battery_storages.csv defines the price-dependent battery storage systems with the following schema:

The parameter battery sets the battery in the bidding zone bidding_zone with the maximum storage capacity of capacity(MWh) and the maximum charge power p_max_charge(MW). The parameter tech(LA/LI/RF/SS) sets the technology to one of the following categories used for enrichment of missing optional values and grouping components in the output.

Additionally, 30_battery_storages.csv can define the following optional discharge, efficiency, state and cost parameters:

p_max_discharge_opt(MW) customizes the maximum discharge power, efficiency_charge_opt(%) the charge efficiency and efficiency_discharge_opt(%) the discharge efficiency. Efficiencies do not influence the maximum power, but changes in the state of charge resulting from charging and discharging. self_discharge_opt(%/h) defines the discharge rate of the current absolute state of charge. The parameters state_of_charge_start_opt(MWh) and state_of_charge_end_opt(MWh) define the absolute state of charge at start and end of the simulation time frame. Further, variable cost for discharging and charging can be defined via cost_opt(EUR/MWh).

Additionally, 30_battery_storages.csv can define the following optional reserve parameters:

p_max_fcr_opt(MW) defines the maximum symmetric Frequency Containment Reserve (FCR) provision of the battery. p_max_afrr_pos_opt(MW) and p_max_afrr_neg_opt(MW) set the maximum positive and negative automatic Frequency Restoration Reserve (aFRR) provision. p_max_mfrr_pos_opt(MW) and p_max_mfrr_neg_opt(MW) set the maximum positive and negative manual Frequency Restoration Reserve (mFRR) provision. Reserve product signs are in line with the generator reference-arrow system, so positive reserve provisions require discharging potentials and negative reserve provisions require charging potentials. To simulate more than one reserve per direction (e.g., more than one positive and one negative quality) or to simulate the FCR, the detailed reserve module must be activated in the configuration via parameter demand_reserves_high_resolution.

Battery mustruns, outages and revisions

31_battery_mustruns_outages_revisions.csv defines exogenous mustruns, outages, and revisions of battery storages with the following schema:

Additionally, 31_battery_mustruns_outages_revisions.csv can define for every event the following optional parameters:

For the time frame between time_stamp_from and time_stamp_until the maximum charging power is restricted to the values p_max_charge_opt(MW) and the maximum discharging power to p_max_discharge_opt(MW).

Battery states of charge

32_battery_states_of_charge.csv defines optional exogenous must-haves of batteries with the following schema:

Additionally, 32_battery_states_of_charge.csv can define for every event the following optional parameters:

During the time frame between time_stamp_from and time_stamp_until the battery in bidding_zone needs to keep the state of charge between state_of_charge_max_opt(MWh) and state_of_charge_min_opt(MWh).

Battery availabilities

33_battery_availabilities.csv defines the availabilities of battery storages with following schema:

The outage and revision drawing is carried out for every outage and revision cluster defined by bidding_zone and tech(LA/LI/RF/SS) in the system as well as time_stamp_from and time_stamp_until in time. availability(%) defines the average work availability of this cluster.

Additionally, 33_battery_availabilities.csv can define for every outage and revision cluster, the following optional drawing parameters.

The parameters event_duration_expectation_opt(h) and event_duration_deviation_opt(h) define the mean and standard deviation of the normal distribution for outage or revision event durations specified in the file line.

Bioenergy power plants

40_bioenergy_power_plants.csv defines the price-inelastic feed-in of bioenergy power plants per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. It has the same format as the spot market demand.

Solar power plants

50_solar_power_plants.csv defines the price-inelastic feed-in of solar power plants per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. It has the same format as the spot market demand.

Wind onshore power plants

60_wind_onshore_power_plants.csv defines the price-inelastic feed-in of wind onshore power plants per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. It has the same format as the spot market demand.

Wind offshore power plants

61_wind_offshore_power_plants.csv defines the price-inelastic feed-in of wind offshore power plants per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. It has the same format as the spot market demand.

Hydro power plants

70_hydro_power_plants.csv defines hydro turbines and hydro pumps with the following non-optional entries:

The parameter connection states a component where hydro flows can occur from reservoir_from to reservoir_to. The parameter tech(FT/FP/PT/KT) sets the technology to one of the following categories used for enrichment of missing optional values and grouping components in the output.

Francis turbines with pump possibility via reverse spin need to be defined with two rows (FT and FP). Francis turbines without using the pump possibility need to be defined with one row (only FT). p_max(MW) customizes the net maximum power for the spot market.

Additionally, 70_hydro_power_plants.csv can define the following optional power, efficiency, reserve and cost parameters:

p_min(MW) customizes the net minimum power for the spot market, height_of_fall_opt(m) the height of fall and efficiency_opt(%) the efficiency of the turbine and respectively of the pump. Efficiencies do not influence the maximum power, but set the water-sided maximum flows. p_max_fcr_opt(MW) defines the maximum symmetric Frequency Containment Reserve (FCR) provision of the power plant in on-state. p_max_afrr_pos_opt(MW) and p_max_afrr_neg_opt(MW) set the maximum positive and negative automatic Frequency Restoration Reserve (aFRR) provision of the power plant in on-state. p_max_mfrr_pos_opt(MW) and p_max_mfrr_neg_opt(MW) set the maximum positive and negative manual Frequency Restoration Reserve (mFRR) provision of the power plant in on-state. To simulate more than one reserve per direction (e.g., more than one positive and one negative quality) or to simulate the FCR, the detailed reserve module must be activated in the configuration via parameter demand_reserves_high_resolution. Further, variable generation or consumption cost can be defined via cost_opt(EUR/MWh).

To keep hydro networks solvable at all times, endogenous inflows, overflows (also known as spillover or spillage) and outflows are automatically defined as slack variables. Internally, the optimization sub-problem for hydro has hydro flows and filling levels as decision variables.

Degrees of freedom of decision variables are set automatically based on the defined parameters. At least the connected bidding zone, component name, source and target reservoir, technology and maximum power need to be defined for a turbine or pump. Reservoirs need at least the connected bidding zone, component name and capacity. Missing other optional parameters are internally assumed based on the remaining given assumptions. It is not mandatory to set up cost thresholds and target filling levels for hydro power in the input data. Those would be then the output of the model since market incentives and component characteristics define the opportunity cost of hydro power plants.

Hydro mustruns, outages and revisions

71_hydro_mustruns_outages_revisions.csv defines exogenous mustruns, outages, and revisions of hydro turbines and hydro pumps with the following schema:

Additionally, 71_hydro_mustruns_outages_revisions.csv can define for every event the following optional parameters:

For the time frame between time_stamp_from and time_stamp_until the maximum power is restricted to the values p_max_opt(MW) and p_min_opt(MW).

Hydro reservoirs

72_hydro_reservoirs.csv defines reservoirs with the following schema:

Reservoirs are water sources or sinks of hydro turbines and pumps.

Additionally, 72_hydro_reservoirs.csv can define the following optional capacities:

If capacities are not provided, the reservoir default capacity of zero is assumed. Capacities can be given either in MWh or in m^3. Mixed usage across reservoirs is legitimate (e.g., capacity_opt(MWh) for upper_reservoir and _spatial_capacity_opt(m^3) for lower_reservoir). Providing values in capacity_opt(MWh) and spatial_capacity_opt(m^3) for the same reservoir leads to their addition.

Additionally, 72_hydro_reservoirs.csv can define the following optional state parameters:

Such define the reservoir filling level before and after the optimization time frame. If none is set, 50 % filling level according to the maximum is assumed. The leakage factor defines the hourly relative losses of the storage. Leaked water will flow to the lower reservoirs.

Hydro reservoir inflows

73_hydro_reservoir_inflows.csv defines optional exogenous inflows with the following schema:

Inflows can be given either in columns inflow_opt(MWh/h) or spatial_inflow_opt(m^3/h). Such can be given due to rain, snowmelt or (not endogenously modeled) upstream water inflows.

Hydro reservoir filling levels

74_hydro_reservoir_filling_levels.csv defines optional exogenous must-haves of reservoirs with the following schema:

Optional must-haves can be given either in MWh or in m^3. MWh and m^3 cannot be defined for a restriction at the same time. Such restrictions can be given for example due to local water resource laws.

Hydro availabilities

75_hydro_availabilities.csv defines the availabilities of hydro turbines and pumps with following schema:

The outage and revision drawing is carried out for every outage and revision cluster defined by bidding_zone and tech(FT/FP/PT/KT) in the system as well as time_stamp_from and time_stamp_until in time. availability(%) defines the average work availability of this cluster.

Additionally, for every outage and revision cluster, the following optional drawing parameters can be set.

The parameters event_duration_expectation_opt(h) and event_duration_deviation_opt(h) define the mean and standard deviation of the normal distribution for outage or revision event durations specified in the file line.

Hydro run of river power plants

79_hydro_run_of_river_power_plants.csv defines the price-inelastic feed-in of run-of-river power plants per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. It has the same format as the spot market demand.

Thermal power plants

80_thermal_power_plants.csv defines thermal turbines with following non-optional entries:

fuel defines the used fuel type and its costs. p_max(MW) sets the technical net maximum power for the spot market and efficiency_p_max_opt(%) the according efficiency. Efficiencies do not influence the maximum power, but set the necessary fuel consumption, emissions and so the generation cost. The parameter tech(CC/GT/ST) sets the technology to one of the following categories used for enrichment of missing optional values and grouping components in the output.

Additionally, 80_thermal_power_plants.csv can define the following optional flexibility and efficiency parameters:

p_min_opt(MW) sets the technical minimum power and efficiency_p_min_opt(%) the according efficiency. on_min_opt(h) and off_min_opt(h) define the minimum time length of on and off states. For modeling combined cycles, the optional parameter unit_downstream_opt can be used. This parameter links two turbines: The turbine with the parameter entry is the upstream unit and the unit to which is referred to is the downstream unit. If this parameter is set, the downstream unit can be one in operation jointly with the upstream unit. If the upstream unit is off, the downstream unit will be off as well. The upstream unit can be freely in operation, if it is not considered a downstream unit from any other unit. Upstream and downstream units can be defined freely to simulate complex combined cycle gas and steam turbine systems.

Additionally, 80_thermal_power_plants.csv can define the following optional reserve parameters:

p_max_fcr_opt(MW) defines the maximum symmetric Frequency Containment Reserve (FCR) provision of the power plant in on-state. p_max_afrr_pos_opt(MW) and p_max_afrr_neg_opt(MW) set the maximum positive and negative automatic Frequency Restoration Reserve (aFRR) provision of the power plant in on-state. p_max_mfrr_pos_opt(MW) and p_max_mfrr_neg_opt(MW) set the maximum positive and negative manual Frequency Restoration Reserve (mFRR) provision of the power plant in on-state. For off-state p_max_mfrr_pos_start_opt(MW) defines the maximum positive mFRR contribution. To simulate more than one reserve per direction (e.g., more than one positive and one negative quality) or to simulate the FCR, the detailed reserve module must be activated in the configuration via parameter demand_reserves_high_resolution.

Additionally, 80_thermal_power_plants.csv can define the following optional cost parameters:

cost_add_opt(EUR/MWh) and cost_add_opt(EUR/h) define the additional variable operation and maintenance costs (additional to fuel, transportation, emission allowance and start-up). cost_start_opt(EUR/start) defines the fixed costs per start-up (not dependent on previous state). fuel_cold_start_opt(GJ/start) defines the additional fuel costs per start-up. cooling_time_constant_opt(h) the cooling time constant. Depending on the state off time (cooling time), the variable start costs are defined together by fuel_cold_start_opt(GJ/start) and cooling_time_constant_opt(h).

Additionally, 80_thermal_power_plants.csv can define the following optional start and end state parameters:

state_before_opt(0/1) and state_after_opt(0/1) define the state of the power plant before and after the total optimization time frame set in the configuration file. state_time_before_opt(h) and state_time_after_opt(h) define the number of hourly time intervals during that state.

Thermal fuel prices

81_thermal_prices_fuel.csv defines fuel costs for power plant operators with the following schema:

price(EUR/GJ) sets the fuel price for the defined fuel during the period between time_stamp_from and time_stamp_until. Fuel names should begin with NUC (nuclear), LIG (lignite), HCO (hard coal), GAS (gas), OIL (oil) or OTH (other) followed by an unsigned integer value (fuel number). Fuel numbers can be used to distinguish types, qualities and locations. The cost paid for the transportation of the fuel to the plant location can be set with price_transport_opt(EUR/GJ). To model different emission intensities, carbon capture and storage (CCS) or carbon capture and utilization (CCU) the emission_intensity_opt(tCO2/GJ) can be set accordingly.

Thermal emission prices

82_thermal_prices_emission.csv defines the costs for emission allowances of power plant operators with the following schema:

price(EUR/tCO2) sets the price during the period between time_stamp_from and time_stamp_until.

Emission restrictions can be used to simulate partially the European Union Emission Trading Scheme (EU ETS).

Thermal mustruns, outages and revisions

83_thermal_mustruns_outages_revisions.csv defines exogenous mustruns of thermal turbines with the following schema:

Additionally, 83_thermal_mustruns_outages_revisions.csv can define for every event the following optional parameters:

For the selected time frame between time_stamp_from and time_stamp_until the power is restricted to the values between p_max_opt(MW) and p_min_opt(MW).

Mustruns can be reasoned for example by heat utility restrictions of plants with combined heat and power.

Outages can be set manually in this 83_thermal_mustruns_outages_revisions.csv or derived during preprocessing in 86_thermal_availabilities.csv. Both are optional and can be used at the same time.

Revisions can be set manually in this 83_thermal_mustruns_outages_revisions.csv or derived during preprocessing in 86_thermal_availabilities.csv. Both are optional and can be used at the same time.

Thermal fuel restrictions

84_thermal_restrictions_fuel.csv defines time-coupled fuel consumption restrictions with the following schema:

Additionally, 84_thermal_restrictions_fuel.csv can specify following optional parameters:

If an fuel restriction specifies minimum and maximum values, the thermal power plants using the linked fuel have to consume the fuel within the defined range.

The restriction GAS_AL_CAP limits for the selected time frame between time_stamp_from and time_stamp_until, the consumption of the fuel GAS1 to the range between min_opt(TJ) and max_opt(TJ). Fuel restrictions can be defined for multiple bidding zones, fuels and time ranges. Such can be reasoned for example due to take-or-pay agreements of long-term natural gas purchase contracts or international fuel import embargos.

Thermal emission restrictions

85_thermal_restrictions_emission.csv defines time-coupled emission caps and floors with the following schema:

Additionally, 85_thermal_restrictions_emission.csv can specify following optional parameters:

If an emission restriction specifies minimum and maximum values, the thermal power plants using the linked fuel have to emit within the defined range.

The restriction CO2_CAP covers the emissions in bidding_zones (in example DE and FR) in the according time frames time_stamp_from and time_stamp_until (in example hour 1 until 8760). The total emissions in this region and time frame need to be between min_opt(tCO2) and max_opt(tCO2). Emission restrictions can be defined for multiple bidding zones and time ranges. The maximum emission amount can be set up to simulate for example the European Union Emission Trading Scheme (EU ETS).

The volume-limiting approach in 85_thermal_restrictions_emission.csv can be combined with the price-setting approach in 82_thermal_prices_emission.csv. The following graph visualizes the differences between both approaches to simulate the emission allowance market.

Users set up the assumption in the first step, the second and third steps are taking place automatically inside the market simulation. The last fourth step comprises direct look-ups in the model output.

Thermal availabilities

86_thermal_availabilities.csv defines outage and revision availabilities as drawing parameters for the preprocessing drawing procedure with the following schema:

The outage and revision drawing is carried out for every outage and revision cluster defined by bidding_zone, tech(CC/GT/ST) and fuel_short in the system as well as time_stamp_from and time_stamp_until in time. availability(%) defines the average work availability of this cluster. fuel_short summarizes all fuels with identical fuel name beginnings (GAS1, GAS2, GAS3, etc., would be put in this example into one drawing cluster GAS).

Additionally, for every outage and revision cluster, the following optional drawing parameters can be set.

event_duration_expectation_opt(h) and event_duration_deviation_opt(h) define the mean and variance of the normal distribution for time ranges of outage and revisions.

Thermal cogeneration power plants

89_thermal_cogeneration_plants.csv defines the price-inelastic electric feed-in of cogeneration plants per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. It has the same format as the spot market demand.

Bidding zones

90_grid_bidding_zones.csv defines bidding zones with the following non-optional entries:

Binary operators activate 1 (default) or deactivate 0 sub-models in the selected bidding_zone. Corresponding input data will be neglected and not checked by the procedure.

Net transfer capacities

91_grid_ntcs.csv defines Net Transfer Capacities (NTC) with the following schema:

The NTC is valid between time_stamp_from and time_stamp_until with a maximum commercial flow of net_transfer_capacity(MW) from from_bidding_zone to to_bidding_zone. The wheeling charge, hurdle rate or exchange cost can be set via cost_opt(EUR/MWh).

Coordinated net transfer capacities

92_grid_cntcs.csv defines Coordinated Net Transfer Capacities (CNTC) with the following schema:

The CNTC is valid between time_stamp_from and time_stamp_until with a commercial exchange capacity(MW) from from_bidding_zone to to_bidding_zone1 and to to_bidding_zone2 together. Further destination bidding zones can be set freely via columns to_bidding_zone3_opt, to_bidding_zone4_opt and so on. A positive capacity value limits the maximum export of the bidding zone specified in from_bidding_zone. A negative capacity value limits the maximum import of the bidding zone specified in from_bidding_zone.

FBMC CNECs

93_grid_fbmc_cnecs.csv defines the flow-based market coupling (FBMC) through critical network elements and contingencies (CNEC) with the following exemplary schema:

A CNEC is valid between time_stamp_from and time_stamp_until with a remaining available margin (RAM). The FBMC domain comprises the bidding zones occurring in the header specifiers (BE, DE, FR and NL in the exemplary table above). By default all bilateral exchanges between bidding zones in the FBMC domain are not limited and so limitations for inner FBMC domain exchanges need to be set explicitly. That applies also for physically not possible bilateral exchanges through zero NTC (for example between FR and NL). The zonal power transfer distribution factor (PTDF) has to be defined for all bidding zones in the FBMC domain. Exchanges between bidding zones are bound by CNEC restrictions. In case of time and or system overlaps with NTC restricted zone pairs, set the according NTC in 91_grid_ntcs.csv or CNTC in 92_grid_cntcs.csv to use combined exchange models.

FBMC AHCs

94_grid_fbmc_ahcs.csv defines advanced hybrid couplings (AHC) with the following schema:

The defined AHC influences the selected CNEC with the zone-to-zone PTDF power_transfer_distribution_factor.

The optional setting evolved_opt enables to exclude the flow to contribute to the CNEC utilizations based in the zonal PTDF, that are derived from 93_grid_fbmc_cnecs.csv. Instead, the zone-to-zone PTDF from 94_grid_fbmc_ahcs.csv is used to calculate the contribution to the utilization of the linked CNEC. This can be used for example to model High-Voltage Direct Current (HVDC) lines and terminals.

Exchange capacities for reserves

95_grid_reserve_exchanges.csv defines bilateral frequency reserve exchange capacities with the following schema:

The symmetric Frequency Containment Reserve (FCR) can be exported between time_stamp_from and time_stamp_until from from_bidding_zone to to_bidding_zone for the exchange cost of cost_opt(EUR/MWh). Via ntc_competition_opt(0/1) reserve exchanges compete with bilateral spot exchanges for NTC capacities in a co-optimization (1 as default) or are handled separately so a spot and reserve exchange can together exceed the according NTC value. To model reserve core shares (total reserve export restrictions) use virtual export bidding zones: create a new bidding zone, disable in this new bidding zone all modules in 90_grid_bidding_zones.csv, parameterize the maximum reserve export inclusive core share to that new bidding zone and set higher total reserve export possibilities from the new virtual bidding zone to other bidding zones. To use the reserve exchange module, the detailed reserves must be activated in the configuration via parameter demand_reserves_high_resolution.

Exchange mustruns, outages and revisions

96_grid_mustruns_outages_revisions.csv defines exogenous mustruns, outages, and revisions of bilateral exchanges with the following schema:

Additionally, 96_grid_mustruns_outages_revisions.csv can define for every event the following optional parameters:

For the time frame between time_stamp_from and time_stamp_until the maximum power is restricted to the values p_max_opt(MW) and p_min_opt(MW).

Grid availabilities

97_grid_availabilities.csv defines the availabilities of exchange capacities with following schema:

The outage and revision drawing is carried out for every outage and revision cluster defined by bidding_zone and type_coupling(NTC/CNTC/FBMC) in the system as well as time_stamp_from and time_stamp_until in time. availability(%) defines the average work availability of this cluster.

Additionally, for every outage and revision cluster, the following optional drawing parameters can be set.

The parameters event_duration_expectation_opt(h) and event_duration_deviation_opt(h) define the mean and standard deviation of the normal distribution for outage or revision event durations specified in the file line.

External spot exports

98_grid_external_exports.csv defines the price-inelastic feed-in of external spot exports per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. It has the same format as the spot market demand.

External spot imports

99_grid_external_imports.csv defines the price-inelastic feed-in of external spot imports per bidding zone. The file format can be obtained via exporting the current dataset at the input export in the front-end. It has the same format as the spot market demand.

Resolution

Generation, consumption and exchange components can be aggregated to perform fast runs. Aggregations are carried out during the preprocessing (see preprocessing) and are based on performant, deterministic and automated schema identification, clustering and aggregation methods. The total joint aggregation time lies for transmission planning level data at below 1 second, but the total optimization complexity can be reduced gradually by magnitudes and so total simulation procedure times can be reduced to below 5 minutes even for very complex scenarios (more than 100000000 components and 8760 hours).

The original input and output data can be processed each bidding zone individually via 90_grid_bidding_zones.csv. Following optional preprocessing, procedure and postprocessing parameters can be defined in 90_grid_bidding_zones.csv:

The parameter battery_aggregation_opt specifies the aggregation level for all batteries in that bidding zone. battery_aggregation_opt can be set between 0 for no aggregation (default) and 1 for one replacement component for each bidding zone (see battery aggregation). The parameter hydro_aggregation_opt specifies the aggregation level for all hydro power plants in that bidding zone. hydro_aggregation_opt can be set between 0 for no aggregation (default) and 8 for one replacement component for each bidding zone (see hydro aggregation). The parameter thermal_aggregation_opt specifies the aggregation level for all thermal power plants in that bidding zone. thermal_aggregation_opt can be set between 0 for no aggregation (default) and 3 for one replacement component for each bidding zone (see thermal aggregation). Other aggregations for grid capacities (exchanges) and flexible demand components (DSR) are currently in development and will be released soon.

The identifier bz_group_id_opt groups bidding zones, so that those in the same group are simulated together in the second procedure step to achieve a more realistic unit commitment (especially on and off states) in smaller bidding zones (see procedure). The binary parameter integral_opt activates 1 or deactivates 0 (default) the write-out of the Integral input dataset (FGH GmbH).