Electric System Input Data

All the input files must be in a folder with the name of the case study.

Acronyms

Acronym	Description
AC	Alternating Current
aFRR	Automatic Frequency Restoration Reserve (a.k.a. secondary reserve) reserve provided within 5 minutes (Full Activation Time)
AWE	Alkaline Water Electrolyzer (consumes electricity to produce hydrogen)
BESS	Battery Energy Storage System
CAPEX	Capital Expenditure
CC	Capacity Credit (contribution of a power generation resource —particularly variable renewable energy (VRE) like wind or solar— to meeting peak demand)
CCGT	Combined Cycle Gas Turbine
CHP	Combined Heat and Power. Cogeneration (produces electricity and heat simultaneously)
DC	Direct Current
DCPF	DC Optimal Power Flow
DR	Demand Response (e.g., interruptibility)
DSM	Demand-Side Management (e.g., load shifting)
DSR	Demand-Side Response (e.g., interruptibility)
EB	Electric Boiler (Power to Heat: consumes electricity to produce heat)
EHU	Electrical Heating Unit (Power to Heat: consumes electricity to produce heat, e.g., heat pump, electric boiler)
EFOR	Equivalent Forced Outage Rate (probability that a generating unit will be unavailable due to forced outages during a given period)
ELCC	Effective Load-Carrying Capability. Amount of additional load that the power system can serve with the inclusion of the resource, while maintaining the same level of system reliability
ELZ	Electrolyzer (Power to Hydrogen: consumes electricity to produce hydrogen)
ENS	Energy Not Served
ENTSO-E	European Network of Transmission System Operators for Electricity
ESS	Energy Storage System
EV	Electric Vehicle
FCE	Firm Capacity Equivalent (amount of reliable, always-available generation capacity that would provide the same level of system reliability as the resource being evaluated)
FHU	Fuel Heating Unit (Fuel to Heat: consumes any fuel other than hydrogen to produce heat, e.g., biomass/natural gas/oil boiler)
GEP	Generation Expansion Planning
H2	Hydrogen
HHU	Hydrogen Heating unit (Hydrogen to Heat: consumes hydrogen to produce heat)
HNS	Hydrogen Not Served
HP	Heat Pump (Power to Heat: consumes electricity to produce heat)
HTNS	Heat Not Served
IRP	Integrated Resource Planning
LCOE	Levelized Cost of Electricity
mFRR	Manual Frequency Restoration Reserve (a.k.a. tertiary reserve) helps to restore the required grid frequency of 50 Hz. It must be fully deployable after 12.5 minutes and has a minimum duration period of 5 minutes
NTC	Net Transfer Capacity (maximum power transfer between two nodes, zones, areas, or regions, considering the network constraints)
OCGT	Open Cycle Gas Turbine
PHS	Pumped-Hydro Storage
PNS	Power Not Served
PTDF	Power Transfer Distribution Factor (ratio of the change in flow on a transmission line to the change in power injection at a node)
PV	Photovoltaics
RES	Renewable Energy Source
SEP	Storage Expansion Planning
TEP	Transmission Expansion Planning
TTC	Total Transfer Capacity (maximum amount of electric power that can be transferred over the transmission network between two areas under ideal operating conditions, while maintaining system security as defined by operational standards)
VoLL	Value of Lost Load (maximum amount of money that a customer is willing to pay to avoid an interruption of 1 kWh of electricity supply). Common values are between 1000 and 10000 €/MWh
VRE	Variable Renewable Energy
VRES	Variable Renewable Energy Source (units with null linear variable cost and no storage capacity. Do not contribute to the operating reserves)

Dictionaries. Sets

The dictionaries include all the possible elements of the corresponding sets in the optimization problem. You can’t use non-English characters (e.g., ó, º)

File	Description
oT_Dict_Period.csv	Period (e.g., 2030, 2035). It must be a positive integer
oT_Dict_Scenario.csv	Scenario. Short-term uncertainties (scenarios) (e.g., s001 to s100, CY2025 to CY2030)
oT_Dict_Stage.csv	Stage
oT_Dict_LoadLevel.csv	Load level (e.g., 01-01 00:00:00+01:00 to 12-30 23:00:00+01:00). If is a datetime format. Load levels with duration 0 are ignored. 8736 load levels must represent the period (year).
oT_Dict_Generation.csv	Generation units (thermal -nuclear, CCGT, OCGT, coal-, ESS -storage hydro modeled in energy or water, pumped-hydro storage PHS, battery BESS, electric vehicle EV, demand side management DSM, data center flexibility, alkaline water electrolyzer AWE, solar thermal- and VRES -wind onshore and offshore, solar PV, run-of-the-river hydro-)
oT_Dict_Technology.csv	Generation technologies. The technology order is used in the temporal result plot.
oT_Dict_Storage.csv	ESS storage type (daily <12 h, weekly <40 h, monthly >60 h).
oT_Dict_Node.csv	Nodes. A node belongs to a defined zone. All the nodes must have a different name. Nodes can be physical or virtual (e.g., for representing the conventional industrial, commercial and residential demands, EV demand, and H2 demand).
oT_Dict_Zone.csv	Zones. A zone belongs to a defined area. All the zones must have a different name.
oT_Dict_Area.csv	Areas. An area belongs to a defined region. All the areas must have a different name. Long-term adequacy, inertia, and operating reserves are associated with areas.
oT_Dict_Region.csv	Regions (e.g., Continental South West Europe which includes Spain, France, and Portugal). All the regions must have a different name.
oT_Dict_Circuit.csv	Circuits (e.g., ac1, ac2 for AC lines, dc1 for DC lines). All the circuits must have a different name.
oT_Dict_Line.csv	Line type (AC, DC)

Assignment of nodes to zones, zones to areas, and areas to regions.

File	Dictionary	Description
oT_Dict_NodeToZone.csv	NodeToZone	Assignment of nodes at zones
oT_Dict_ZoneToArea.csv	ZoneToArea	Assignment of zones at areas
oT_Dict_AreaToRegion.csv	AreaToRegion	Assignment of areas at regions

See the hydropower system section at the end of this page to learn how to define the basin topology (connection among reservoirs and hydropower plants). Some additional dictionaries and data files are needed.

Input files

This is the list of the input data files and their brief description.

File	Description
oT_Data_Option.csv	Options of use of the openTEPES model
oT_Data_Parameter.csv	General system parameters
oT_Data_Period.csv	Weight of each period
oT_Data_Scenario.csv	Short-term uncertainties
oT_Data_Stage.csv	Weight of each stage
oT_Data_ReserveMargin.csv	Minimum adequacy reserve margin for each area and period
oT_Data_Emission.csv	Maximum CO2 emissions of the electric system
oT_Data_RESEnergy.csv	Minimum RES energy for each area and period
oT_Data_Duration.csv	Duration of the load levels
oT_Data_Demand.csv	Electricity demand
oT_Data_Inertia.csv	System inertia by area
oT_Data_OperatingReserveUp.csv	Upward operating reserves (include aFRR and mFRR for electricity balancing from ENTSO-E)
oT_Data_OperatingReserveDown.csv	Downward operating reserves (include aFRR and mFRR for electricity balancing from ENTSO-E)
oT_Data_OperatingReserveUpEnergy.csv	Upward operating reserves activation (include aFRR and mFRR for electricity balancing from ENTSO-E) (optional file)
oT_Data_OperatingReserveDownEnergy.csv	Downward operating reserves activation (include aFRR and mFRR for electricity balancing from ENTSO-E) (optional file)
oT_Data_RampReserveUp.csv	Upward ramp reserves (optional file)
oT_Data_RampReserveDown.csv	Downward ramp reserves (optional file)
oT_Data_Generation.csv	Generation (electricity and heat) data
oT_Data_VariableMaxGeneration.csv	Variable maximum power generation by load level
oT_Data_VariableMinGeneration.csv	Variable minimum power generation by load level
oT_Data_VariableMaxConsumption.csv	Variable maximum power consumption by load level
oT_Data_VariableMinConsumption.csv	Variable minimum power consumption by load level
oT_Data_VariableFuelCost.csv	Variable fuel cost by load level
oT_Data_EnergyInflows.csv	Energy inflows into an ESS by load level
oT_Data_EnergyOutflows.csv	Energy outflows from an ESS for Power-to-X (H2 production, EV mobility, heat production, or water irrigation) by load level
oT_Data_VariableMaxStorage.csv	Maximum amount of energy stored in the ESS by load level
oT_Data_VariableMinStorage.csv	Minimum amount of energy stored in the ESS by load level
oT_Data_VariableMaxEnergy.csv	Maximum amount of energy produced/consumed by the unit by time interval (the amount of energy considered corresponds to the aggregate over the interval defined by EnergyType)
oT_Data_VariableMinEnergy.csv	Minimum amount of energy produced/consumed by the unit by time interval (the amount of energy considered corresponds to the aggregate over the interval defined by EnergyType)
oT_Data_Network.csv	Electricity network data
oT_Data_VariableTTCFrw.csv	Maximum electric transmission line TTC forward flow by load level (optional file)
oT_Data_VariableTTCBck.csv	Maximum electric transmission line TTC backward flow by load level (optional file)
oT_Data_NodeLocation.csv	Node location in latitude and longitude

Only the columns indicated in this document will be read in any input file. For example, you can add a column for comments or additional information as needed, but the model will not read it.

Options

A description of the options included in the file oT_Data_Option.csv follows:

Item	Description
IndBinGenInvest	Indicator of binary generation expansion decisions	{0 continuous, 1 binary, 2 ignore investments}
IndBinGenRetirement	Indicator of binary generation retirement decisions	{0 continuous, 1 binary, 2 ignore retirements}
IndBinRsrInvest	Indicator of binary reservoir expansion decisions (only used for reservoirs modeled with water units)	{0 continuous, 1 binary, 2 ignore investments}
IndBinNetInvest	Indicator of binary electricity network expansion decisions	{0 continuous, 1 binary, 2 ignore investments}
IndBinNetH2Invest	Indicator of binary hydrogen network expansion decisions	{0 continuous, 1 binary, 2 ignore investments}
IndBinNetHeatInvest	Indicator of binary heat network expansion decisions	{0 continuous, 1 binary, 2 ignore investments}
IndBinGenOperat	Indicator of binary generation operation decisions	{0 continuous, 1 binary}
IndBinGenRamps	Indicator of considering or not the up/down ramp constraints	{0 no ramps, 1 ramp constraints}
IndBinGenMinTime	Indicator of considering or not the min up/down time constraints	{0 no min time constraints, 1 min time constraints}
IndBinSingleNode	Indicator of single node case study	{0 network, 1 single node}
IndBinLineCommit	Indicator of binary transmission switching decisions	{0 continuous, 1 binary}
IndBinNetLosses	Indicator of network losses	{0 lossless, 1 ohmic losses}

Suppose the investment decisions are ignored (IndBinGenInvest, IndBinGenRetirement, and IndBinNetInvest take value 2) or there are no investment decisions. In that case, all the scenarios with a probability >0 are solved sequentially (assuming a probability of 1), and the periods are considered with a weight of 1.

If you select the single node option (IndBinSingleNode takes value 1), the line capacity constraints are relaxed (i.e., flows can exceed these capacities), but line flows are obtained and presented in the result files. The line losses are considered 0.

Parameters

A description of the system parameters included in the file oT_Data_Parameter.csv follows:

Item	Description
ENSCost	Cost of energy not served (ENS). Cost of load curtailment. Value of Lost Load (VoLL)	€/MWh
HNSCost	Cost of hydrogen not served (HNS). The cost of the H2 surplus is half of this value	€/kgH2
HTNSCost	Cost of heat not served (HTNS)	€/MWh
CO2Cost	Cost of CO2 emissions	€/tCO2
UpReserveActivation	Upward reserve activation (proportion of upward operating reserve deployed to produce energy, e.g., 0.15)	p.u.
DwReserveActivation	Downward reserve activation (proportion of downward operating reserve deployed to produce energy, e.g., 0.10)	p.u.
MinRatioDwUp	Minimum ratio downward to upward operating reserves	p.u.
MaxRatioDwUp	Maximum ratio downward to upward operating reserves	p.u.
Sbase	Base power used in the DCPF	MW
ReferenceNode	Reference node used in the DCPF
TimeStep	Number of time steps grouped together. If the duration is 1 h and the time step is 2, two consecutive hours are grouped into one load level for the optimization problem. If the duration is 0.25 h and the time step is 4, the load level represents one hour.
EconomicBaseYear	Base year for economic parameters affected by the discount rate	year
AnnualDiscountRate	Annual discount rate	p.u.

A time step greater than one hour is a convenient way to reduce the load levels of the time scope. The moving average of the demand, upward/downward operating reserves, variable generation/consumption/storage, and ESS energy inflows/outflows over the time step load levels is assigned to active load levels (e.g., the mean value of the three hours is associated with the third hour in a trihourly time step).

Generators can provide upward and downward operating reserves simultaneously. The upward and downward activation proportions define the amount of upward and downward operating reserves that will be deployed to produce energy. In case of having both upward and downward operating reserves, the activation of both may cancel the energy produced.

Period

A description of the data included in the file oT_Data_Period.csv follows:

Identifier	Header	Description
Period	Weight	Weight of each period

This weight allows the definition of equivalent (representative) years (e.g., year 2030 with a weight of 5 would represent years 2030-2034). Periods are not mathematically connected between them with operation constraints, i.e., no constraints link the operation at different periods. However, they are linked by the investment decisions, i.e., investments made in a year remain installed for the rest of the years.

Scenario

A description of the data included in the file oT_Data_Scenario.csv follows:

Identifiers		Header	Description
Period	Scenario	Probability	Probability of each scenario in each period	p.u.

For example, the scenarios can be used for obtaining the IRP (GEP+SEP+TEP) considering hydro energy/water inflows uncertainty represented using three scenarios (wet, dry, and average), or two VRES scenarios (windy/cloudy and calm/sunny). The sum of the probabilities of all the period scenarios must be 1.

Stage

A description of the data included in the file oT_Data_Stage.csv follows:

Identifier	Header	Description
Scenario	Weight	Weight of each stage

This weight defines equivalent (representative) periods (e.g., one representative week weighing 52 or four representative weeks, each weighing 13). Stages are not mathematically connected, i.e., no constraints link the operation at different consecutive stages. Therefore, the storage type can’t exceed the duration of the stage (i.e., if the stage lasts for 168 hours, the storage type can only be hourly or daily). If there are no investment decisions or the investment decisions are ignored, all the periods, scenarios, and stages are solved independently.

Adequacy reserve margin

The adequacy reserve margin is the ratio between the available capacity and the maximum demand. According to ENTSO-E, adequacy is defined as the ability of the electric system to supply the aggregate electrical demand and energy requirements of the customers at all times, taking into account scheduled and reasonably expected unscheduled outages of system elements. To determine the available capacity, the model uses the availability of the generating units times their maximum power. The availability can be computed as the ratio between the firm and installed capacity. Firm capacity can be determined as the Firm Capacity Equivalent (FCE) or the Effective Load-Carrying Capability (ELCC). A description of the data included in the file oT_Data_ReserveMargin.csv follows:

Identifiers		Header	Description
Period	Area	ReserveMargin	Minimum adequacy reserve margin for each period and area	p.u.

This parameter is only used for system generation expansion, not for system operation. If no value is introduced for an area, the reserve margin is considered 0.

Maximum CO2 emissions

A description of the data included in the file oT_Data_Emission.csv follows:

Identifiers		Header	Description
Period	Area	CO2Emission	Maximum CO2 emissions of the electric system for each period and area	MtCO2

If no value is introduced for an area, the CO2 emission limit is considered infinite.

Minimum RES energy

It is like a Renewable Portfolio Standard (RPS). A description of the data included in the file oT_Data_RESEnergy.csv follows:

Identifiers		Header	Description
Period	Area	RESEnergy	Minimum RES energy for each period and area	GWh

If no value is introduced for an area, the RES energy limit is considered 0.

Duration

A description of the data included in the file oT_Data_Duration.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Duration	Duration of the load level. Load levels with duration 0 are ignored. For an hour, the duration must be 1. For quarter on an hour, the duration must be 0.25	h
…	…	…	Stage	Assignment of the load level to a stage

It is a simple way to use isolated snapshots, representative days, or just the first three months instead of all the hours of a year to simplify the optimization problem. All the load levels whose duration is different from 0 must have the same duration. The duration is not intended to change for the load levels of a stage. Usually, duration is 1 hour (0.25 h if inputting data in quarters of an hour) or 0 if you do not want to use the load levels for some hours of the year. The parameter time step must be used to collapse consecutive load levels into one for the optimization problem.

The stage duration, as the sum of the duration of all the load levels, must be larger than or equal to the shortest duration of any storage type, any outflow type, or any energy type (all given in the generation data), and a multiple of it. Consecutive stages are not connected, i.e., no constraints link the operation at different stages. Consequently, the storage type can’t exceed the duration of the stage (i.e., if the stage lasts for 168 hours, the storage type can only be hourly or daily). Consequently, the objective function with several stages must be a bit higher than in the case of a single stage.

The initial storage of the ESSs is also fixed at the beginning and end of each stage. For example, the initial storage level is set for the hour 8736 in case of a single stage or for the hours 4368 and 4369 (end of the first stage and beginning of the second stage) in case of two stages, each with 4368 hours.

Electricity demand

A description of the data included in the file oT_Data_Demand.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Node	Power demand of the node for each load level	MW

The electricity demand can be negative for the (transmission) nodes with (renewable) generation at lower voltage levels. This negative demand is equivalent to generating that power amount in this node. Internally, if positive demand (or above if negative demand) 1e-5 times the maximum system demand of each area, all the values below will be converted into 0 by the model.

System inertia

A description of the data included in the files oT_Data_Inertia.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Area	System inertia of the area for each load level	s

Given that the system inertia depends on the area, assigning an area as a country can be sensible. The system inertia can impose a minimum synchronous power and, consequently, force the commitment of at least some rotating units. Each generating unit can contribute to the system inertia. The system inertia is the sum of the inertia of all the committed units in the area.

Internally, all the values below 1e-5 times the maximum system electricity demand of each area will be converted to 0 by the model.

Upward and downward operating reserves

A description of the data included in the files oT_Data_OperatingReserveUp.csv and oT_Data_OperatingReserveDown.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Area	Upward/downward operating reserves of the area for each load level	MW

Given that the operating reserves depend on the area, assigning an area to a country can be sensible. These operating reserves must include Automatic Frequency Restoration Reserves (aFRR) (a.k.a. secondary reserve, deployed <5 min) and Manual Frequency Restoration Reserves (mFRR) (a.k.a. tertiary reserve, deployed <12.5 min) for electricity balancing from ENTSO-E.

Internally, all the values below 1e-5 times the maximum system demand of each area will be converted into 0 by the model.

Upward and downward operating reserve activation (optional files)

A description of the data included in the files oT_Data_OperatingReserveUpEnergy.csv and oT_Data_OperatingReserveDownEnergy.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Area	Upward/downward operating reserve activation of the area for each load level	MW

Given that the operating reserves depend on the area, assigning an area to a country can be sensible. These operating reserves must include the activation of the Automatic Frequency Restoration Reserves (aFRR) (a.k.a. secondary reserve, deployed <5 min) and Manual Frequency Restoration Reserves (mFRR) (a.k.a. tertiary reserve, deployed <12.5 min) for electricity balancing from ENTSO-E.

The values of the upward/downward operating reserve activation must be lower or equal than the upward/downward operating reserve requirement. If not, they are lowered by the model. Besides, all the values below 1e-5 times the maximum system demand of each area will be converted into 0 by the model.

These files are optional. If not given, the upward and downward operating reserve activation constraints are not formulated. If given, then the parameters UpReserveActivation and DwReserveActivation are not used, and the values of the upward/downward operating reserve activation are directly read from these files.

Upward and downward ramp reserves (optional files)

A description of the data included in the files oT_Data_RampReserveUp.csv and oT_Data_RampReserveDown.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Area	Upward/downward ramp reserves of the area for each load level	MW/h

The ramp reserves are typically associated with a specific additional proportion of the net demand ramp. Ramp reserves protect the system against uncertainty in the VRES production. These files are optional. If not given, the ramp reserve constraints are not formulated.

Generation

A description of the data included for each (electricity and heat) generating unit in the file oT_Data_Generation.csv follows:

Header	Description
Generator	Name of the generator. Each generator must have a unique name.
Node	Name of the node where the generator is located. If left empty or assigned to a non existing node, the generator is ignored
Technology	Technology of the generator (nuclear, coal, CCGT, OCGT, ESS, solar, wind, biomass, etc.)
MutuallyExclusive	List of mutually exclusive sets to which the generator belongs. Only one generator per set can be committed simultaneously. It is computationally demanding.
BinaryCommitment	Binary unit commitment decision	Yes/No
NoOperatingReserve	No contribution to operating reserve. Yes, if the unit doesn’t contribute to the operating reserve	Yes/No
OutflowsIncompatibility	Outflows are incompatible with the charging process (e.g., electric vehicle). This is not the case of an electrolyzer	Yes/No
StorageType	Represents the time period (hour, day, week, month, year) over which the requirement that aggregate electricity production must equal aggregate consumption is enforced. If empty, Hourly by default	Hourly/Daily/Weekly/Monthly/Yearly
OutflowsType	Represents the time period (hour, day, week, month, year) over which the specified amount of energy must be consumed/withdrawn from the storage unit. If empty, Hourly by default	Hourly/Daily/Weekly/Monthly/Yearly
EnergyType	Represents the time period (hour, day, week, month, year) over which the specified max/min amount of energy is to be produced by the unit. If empty, Hourly by default	Hourly/Daily/Weekly/Monthly/Yearly
MustRun	Must-run unit	Yes/No
InitialPeriod	Initial period (year) when the unit is installed or can be installed, if it is a candidate	Year
FinalPeriod	Final period (year) when the unit is installed or can be installed, if it is a candidate	Year
MaximumPower	Maximum power output of electricity (generation/discharge for ESS units)	MW
MinimumPower	Minimum power output of electricity (i.e., minimum stable load in the case of a thermal power plant)	MW
MaximumPowerHeat	Maximum heat output (heat produced by a CHP, at its maximum electric power, or by a fuel heater, which do not produce electric power)	MW
MinimumPowerHeat	Minimum heat output (heat produced by a CHP, at its minimum electric power, or by a fuel heater, which do not produce electric power)	MW
MaximumReactivePower	Maximum reactive power output (discharge for ESS units) (not used in this version)	MW
MinimumReactivePower	Minimum reactive power output (not used in this version)	MW
MaximumCharge	Maximum consumption/charge level when the ESS unit is storing energy	MW
MinimumCharge	Minimum consumption/charge level when the ESS unit is storing energy	MW
InitialStorage	Initial amount of energy stored at the first instant of the time scope	GWh
MaximumStorage	Maximum amount of energy that can be stored by the ESS unit	GWh
MinimumStorage	Minimum amount of energy that can be stored by the ESS unit	GWh
Efficiency	Round-trip efficiency of the pump/turbine cycle of a pumped-hydro storage power plant or charge/discharge of a battery	p.u.
ProductionFunctionHydro	Production function from water inflows (denominator) to electricity (numerator) (only used for hydropower plants modeled with water units and basin topology)	kWh/m3
ProductionFunctionH2	Production function from electricity (numerator) to hydrogen (denominator) (only used for electrolyzers)	kWh/kgH2
ProductionFunctionHeat	Production function from electricity (numerator) to heat (denominator) (only used for heat pumps or electric boilers)	kWh/kWh
ProductionFunctionH2ToHeat	Production function from hydrogen (numerator) to heat (denominator) (only used for hydrogen heater, which produces heat by burning hydrogen)	kgH2/kWh
Availability	Unit availability for area adequacy reserve margin (also called de-rating factor or capacity credit (CC) or Firm Capacity Equivalent (FCE) or the Effective Load-Carrying Capability (ELCC))	p.u.
Inertia	Unit inertia constant	s
EFOR	Equivalent Forced Outage Rate (probability that a generating unit will be unavailable due to forced outages during a given period)	p.u.
RampUp	Maximum rate of increasing its output for generating units, or maximum rate of increasing its discharge rate or decreasing its charge rate for ESS units. If left empty, no ramp up constraint is formulated for the generator.	MW/h
RampDown	Maximum rate of decreasing its output for generating units, or maximum rate of increasing its charge rate or decreasing its discharge rate for ESS units. If left empty, no ramp down constraint is formulated for the generator.	MW/h
MW/h
UpTime	Minimum uptime	h
DownTime	Minimum downtime	h
StableTime	Minimum stable time (intended for nuclear units to be at their minimum load, if lower than the rated capacity, during this time). Power variations (ramp up/ramp down) below 1% are not considered for activating the minimum stable time	h
ShiftTime	Maximum shift time	h
FuelCost	Fuel cost	€/GJ
LinearTerm	Linear term (slope) of the heat rate straight line	GJ/MWh
ConstantTerm	Constant term (intercept) of the heat rate straight line	GJ/h
OMVariableCost	Variable O&M cost	€/MWh
OperReserveCost	Operating reserve cost	€/MW
StartUpCost	Startup cost	M€
ShutDownCost	Shutdown cost	M€
CO2EmissionRate	CO2 emission rate. It can be negative for units absorbing CO2 emissions as biomass	tCO2/MWh
FixedInvestmentCost	Overnight investment (capital -CAPEX- and fixed O&M -FOM-) cost	M€
FixedRetirementCost	Overnight retirement (capital -CAPEX- and fixed O&M -FOM-) cost	M€
FixedChargeRate	Fixed-charge rate to annualize the overnight investment cost. Proportion of annual payment to return the overnight investment cost	p.u.
StorageInvestment	Storage capacity and energy inflows are proportional to the investment decision. For example, in a battery with 4 h duration, the storage capacity will be proportional to the power invested. In a candidate reservoir, the size is usually predetermined and can’t be made proportional to the investment decision.	Yes/No
BinaryInvestment	Binary unit investment decision	Yes/No
InvestmentLo	Lower bound of investment decision	p.u.
InvestmentUp	Upper bound of investment decision	p.u.
BinaryRetirement	Binary unit retirement decision	Yes/No
RetirementLo	Lower bound of retirement decision	p.u.
RetirementUp	Upper bound of retirement decision	p.u.

The main characteristics that define each type of generator are the following:

Generator type	Description	Set name
Any generator	It has MaximumPower or MaximumCharge or MaximumPowerHeat >0	g
Thermal	Fuel-based variable cost (fuel cost x linear term + CO2 emission cost) >0	t
VRE	Fuel-based variable cost (fuel cost x linear term + CO2 emission cost) =0 and MaximumStorage =0. It may have OMVariableCost >0	re
Non-renewable	All the generators except the RESS	nr
ESS	It has MaximumCharge or MaximumStorage >0 or ProductionFunctionH2 or ProductionFunctionHeat >0 and ProductionFunctionHydro =0	es
Hydro power plant (energy)	ESS with ProductionFunctionHydro =0	es
Pumped-hydro storage (energy)	ESS with MaximumCharge >0 and MaximumStorage >0	es
Battery (BESS), load shifting (DSM)	ESS with MaximumCharge >0 and MaximumStorage >0 (usually, StorageType daily)	es
Data center flexibility	ESS with MaximumCharge >0 and MaximumStorage >0 (usually, StorageType daily)	es
Electric vehicle (EV)	ESS with electric energy outflows	es
Electrolyzer (ELZ)	ESS with electric energy outflows and ProductionFunctionH2 >0 and ProductionFunctionHeat =0 and ProductionFunctionHydro =0	el
Heat pump or electric boiler	ESS with ProductionFunctionHeat >0 and ProductionFunctionH2 =0 and ProductionFunctionHydro =0	hp
CHP or fuel heating unit	It has RatedMaxPowerElec >0 and RatedMaxPowerHeat >0 and ProductionFunctionHeat =0	ch
Fuel heating unit, fuel boiler	It has RatedMaxPowerElec =0 and RatedMaxPowerHeat >0 and ProductionFunctionHeat =0	bo
Hydrogen heating unit	Fuel heating unit with ProductionFunctionH2ToHeat >0	hh
Hydro power plant (water)	It has ProductionFunctionHydro >0	h
Reservoir (water)	It has water volume	rs

The model always considers a month of 672 hours, i.e., 4 weeks, not calendar months. The model assumes a year of 8736 hours, i.e., 52 weeks, not calendar years.

Daily storage type means the ESS inventory is assessed at every step. Daily storage type is assessed at the end of every hour, weekly storage type is assessed at the end of every day, monthly storage type is assessed at the end of every week, and the yearly storage type is evaluated at the end of every month. Outflows type represents when the energy extracted from the storage must be satisfied (for daily outflows type at the end of every day, i.e., the sum of the energy consumed must be equal to the sum of outflows daily). The contribution of EVs and electrolyzers to the system flexibility can be analyzed by changing the outflows type (from hourly to daily or weekly or monthly or yearly). Energy type represents when the minimum or maximum energy to be produced by a unit must be satisfied (for daily energy type at the end of every day, i.e., the sum of the energy generated by the unit must be lower/greater than the sum of max/min energy for every day). The storage cycle is the minimum between the inventory assessment period (defined by the storage type), the outflows period (defined by the outflows type), and the energy period (determined by the energy type) (only if outflows or energy power values have been introduced). It can be one time step, day, week, or month, but it can’t exceed the stage duration. For example, if the stage lasts 168 hours, the storage cycle can only be hourly or daily.

The initial storage of the ESSs is also fixed at the beginning and end of each stage, only if the initial inventory lies between the storage limits. For example, the initial storage level is set for the hour 8736 in case of a single stage or for the hours 4368 and 4369 (end of the first stage and beginning of the second stage) in case of two stages, each with 4368 hours.

A generator with operation cost (sum of the fuel and emission cost, excluding O&M cost) >0 is considered a non-renewable unit. If the unit has no operation cost and its maximum storage =0, It is considered a renewable unit. If its maximum storage is >0, with or without operation cost, it is regarded as an ESS.

A very small variable O&M cost (not below 0.01 €/MWh, otherwise it will be converted to 0 by the model) for the ESS can be used to avoid pumping with avoided curtailment (at no cost) and afterwards discharged as spillage.

The startup cost of a generating unit refers to the expenses incurred when bringing a power generation unit online, from an idle state to a point where it can produce electricity.

Must-run non-renewable units are always committed, i.e., their commitment decision equals 1. All must-run units are forced to produce at least their minimum output.

EFOR is used to reduce the maximum and minimum power of the unit. For hydropower plants, it can be used to reduce their maximum power by the water head effect. It does not reduce the maximum charge.

Those generators or ESS with fixed cost >0 are considered candidates and can be installed. The fixed cost is the product of the overnight investment cost (FixedInvestmentCost) and the fixed charge rate (FixedChargeRate).

Maximum, minimum, and initial storage values are considered proportional to the invested capacity for the candidate ESS units if StorageInvestment is activated (Yes). This can be used for battery investment decisions where the investment can be continuous (StorageInvestment=Yes). For a particular hydro storage investment the dam investment is linked to this particular hydro and can’t be made proportional (StorageInvestment=No).

A generator can belong to several mutually exclusive sets; their names must be separated by “|” when inputted. So if Generator1 belongs to Set1 and Set2, the data entry should be “Set1|Set2”. If any of the generators in a group are installation/retirement candidates, it is assumed that exclusivity is yearly, so only one can be committed during the whole period. When all mutually exclusive generators in a set are installed and functioning, it is assumed that the exclusivity is hourly, and which generator is committed can change every load level.

A generator can be restricted to only be able to provide reserves while generating or while consuming. The NoOperatingReserve entry accepts two inputs separated by a “|”. The first value corresponds to operating reserves while generating, and the second is operating reserves while consuming power. If only one value is entered, both values are considered the same. If no value is entered, both values are considered “No”.

If the lower and upper bounds of investment/retirement decisions are very close (with a difference <1e-4) to 0 or 1, they are converted into 0 and 1. To forbid investment or retirement on a candidate, set the corresponding upper bound (InvestmentUp or RetirementUp) to 1e-5: it falls below the snap threshold and is internally converted to 0. A blank cell or 0 in these columns is interpreted as “no upper bound” (full p.u. allowed) and lets the candidate be freely chosen by the optimisation.

A hydrogen import can be represented by means of an electric generator with variable cost equal to the import cost and an electrolyzer with a production function ProductionFunctionH2 equal to 1. This generator must be located in an isolated electricity network (from the main one) and the electrolyzer must be located in a node linking this isolated electricity network and the hydrogen network.

A summary of the main characteristics of the different types of hydro and ESS is shown in the following figure:

Variable maximum and minimum generation

A description of the data included in the files oT_Data_VariableMaxGeneration.csv and oT_Data_VariableMinGeneration.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Generator	Maximum (minimum) power generation of the unit by load level	MW

Not all the generators must be defined as columns of these files, only those with values different from 0.

This information can be used to consider scheduled outages or weather-dependent operating capacity.

To force a generator to produce 0, a small value (e.g., 0.1 MW) strictly >0, but not 0 (in which case the value will be ignored), must be introduced. This is needed to limit the solar production at night, for example. It can also be used for upper-bounding and/or lower-bounding the output of any generator (e.g., run-of-the-river hydro, wind). If the user introduces a minimum generation value greater than the maximum, the model will adjust the minimum generation value to match the maximum.

Internally, all the values below 1e-5 times the maximum system demand of each area will be converted into 0 by the model.

Variable maximum and minimum consumption

A description of the data included in the files oT_Data_VariableMaxConsumption.csv and oT_Data_VariableMinConsumption.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Generator	Maximum (minimum) power consumption of the unit by load level	MW

Not all the generators must be defined as columns of these files, only those with values different from 0.

To force an ESS to consume 0 a value (e.g., 0.1 MW) strictly >0, but not 0 (in which case the value will be ignored), must be introduced. It can also be used for upper-bounding and/or lower-bounding the consumption of any ESS (e.g., pumped-hydro storage, battery, DSM). If the user introduces a maximum consumption value lower than the minimum consumption value, the model will adjust the minimum consumption value to match the maximum.

Internally, all the values below 1e-5 times the maximum system demand of each area will be converted into 0 by the model.

Variable fuel cost

A description of the data included in the file oT_Data_VariableFuelCost.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Generator	Variable fuel cost	€/GJ

Not all the generators must be defined as columns of these files, only those with values different from 0.

Internally, all the values below 1e-4 will be converted into 0 by the model.

Fuel cost affects the linear and constant terms of the heat rate, expressed in GJ/MWh and GJ/h, respectively.

Variable emission cost

A description of the data included in the file oT_Data_VariableEmissionCost.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Generator	Variable emission cost	€/tCO2

Not all the generators must be defined as columns of these files, only those with values different from 0.

Internally, all the values below 1e-4 will be converted into 0 by the model.

Energy inflows

A description of the data included in the file oT_Data_EnergyInflows.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Generator	Energy inflows by load level	MWh/h

Not all the generators must be defined as columns of these files, only those with values different from 0.

If you have daily energy inflow data, just input the daily amount during the first hour of every day to see if the ESS has daily or weekly storage capacity.

Internally, all the values below 1e-5 times the maximum system demand of each area will be converted into 0 by the model.

Energy inflows are considered proportional to the invested capacity for the candidate ESS units if StorageInvestment is activated.

Energy outflows

A description of the data included in the file oT_Data_EnergyOutflows.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Generator	Energy outflows by load level	MWh/h

Not all the generators must be defined as columns of these files, only those with values different from 0.

These energy outflows can represent the electric energy extracted from an ESS to produce H2 from electrolyzers, move EVs, produce heat, or as hydro outflows for irrigation. Using these outflows is incompatible with the charge of the ESS within the same time step (as the discharge of a battery is incompatible with the charge in the same hour).

If you have hourly/daily/weekly/monthly/yearly outflow data, you can just input the hourly/daily/weekly/monthly/yearly amount at the first hour of every day/week/month/year.

Internally, all the values below 1e-5 times the maximum system demand of each area will be converted into 0 by the model.

Variable maximum and minimum storage

A description of the data included in the files oT_Data_VariableMaxStorage.csv and oT_Data_VariableMinStorage.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Generator	Maximum (minimum) storage of the ESS by load level	GWh

Not all the generators must be defined as columns of these files, only those with values different from 0.

It can also be used for upper-bounding and/or lower-bounding the storage of any generator (e.g., storage hydro). If the user introduces a maximum storage value lower than the minimum, the model will adjust the minimum storage value to match the maximum.

For example, these data can define the operating guide (rule) curves for the ESS.

Variable maximum and minimum energy

A description of the data included in the files oT_Data_VariableMaxEnergy.csv and oT_Data_VariableMinEnergy.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Generator	Maximum (minimum) power of the unit by load level	MW

Not all the generators must be defined as columns of these files, only those with values different from 0.

It can also be used for upper-bounding and/or lower-bounding the energy of any generator (e.g., storage hydro). If the user introduces a maximum power value lower than the minimum, the model will adjust the minimum power value to match the maximum.

For example, these data can be used to define the minimum and/or maximum energy to be produced hourly, daily, weekly, monthly, or yearly (depending on the energy type).

Electricity transmission network

At least one electric transmission line connecting two nodes must be defined.

A description of the circuit (initial node, final node, circuit) data included in the file oT_Data_Network.csv follows:

Header	Description
InitialNode	Name of the initial node of the transmission line
FinalNode	Name of the final node of the transmission line
Circuit	Name of the circuit (if there are several circuits between two nodes, they must have different names)
InitialNode	Name of the initial node of the transmission line
LineType	Line type {AC, DC, Transformer, Converter}. AC lines can be subject to Kirchhoff’s second law. DC lines, transformers, and converters are not subject to Kirchhoff’s second law.
Switching	The transmission line can switch on/off	Yes/No
InitialPeriod	Initial period (year) when the unit is installed or can be installed, if candidate	Year
FinalPeriod	Final period (year) when the unit is installed or can be installed, if candidate	Year
Voltage	Line voltage (e.g., 400, 220 kV, 220.400 kV if transformer). Used only for plotting purposes	kV
Length	Line length (only used for reporting purposes). If not defined, computed as 1.1 times the geographical distance	km
LossFactor	Transmission losses equal to the line power flow times this factor	p.u.
Resistance	Resistance (not used in this version)	p.u.
Reactance	Reactance. Lines must have a reactance different from 0 to be considered	p.u.
Susceptance	Susceptance (not used in this version)	p.u.
AngMax	Maximum angle difference (not used in this version)	º
AngMin	Minimum angle difference (not used in this version)	º
Tap	Tap changer (not used in this version)	p.u.
Converter	Converter station (not used in this version)	Yes/No
TTC	Total transfer capacity (maximum permissible thermal load) in forward direction. Static line rating	MW
TTCBck	Total transfer capacity (maximum permissible thermal load) in backward direction. Static line rating	MW
SecurityFactor	Security factor to consider approximately N-1 contingencies (e.g., common values are in the range 0.6-0.7). NTC=TTCxSecurityFactor. All the security factors can’t be 0. Otherwise, there is no capacity network.	p.u.
FixedInvestmentCost	Overnight investment (capital -CAPEX- and fixed O&M -FOM-) cost	M€
FixedChargeRate	Fixed-charge rate to annualize the overnight investment cost	p.u.
BinaryInvestment	Binary line/circuit investment decision	Yes/No
InvestmentLo	Lower bound of investment decision	p.u.
InvestmentUp	Upper bound of investment decision	p.u.
SwOnTime	Minimum switch-on time	h
SwOffTime	Minimum switch-off time	h

The initial and final nodes are where the transmission line starts and ends, respectively. They must be different.

Depending on the voltage, lines are plotted with different colors (orange < 200 kV, 200 < green < 350 kV, 350 < red < 500 kV, 500 < orange < 700 kV, blue > 700 kV).

If there is no data for TTCBck, i.e., TTCBck is left empty or is equal to 0, the TTC substitutes it in the code. Internally, all the TTC and TTCBck values below 1e-5 times the maximum system demand of each area will be converted into 0 by the model.

Reactance can take a negative value due to the approximation of three-winding transformers. No Kirchhoff’s second law disjunctive constraint is formulated for a circuit with negative reactance.

Those lines with fixed cost >0 are considered candidates and can be installed. The fixed cost is the product of the overnight investment cost (FixedInvestmentCost) and the fixed charge rate (FixedChargeRate). The reactance of a candidate line doesn’t change although the candidate line is invested partially.

If the lower and upper bounds of investment decisions are very close (with a difference <1e-4) to 0 or 1, they are converted into 0 and 1. To forbid investment on a candidate line, set InvestmentUp to 1e-5: it falls below the snap threshold and is internally converted to 0. A blank cell or 0 in this column is interpreted as “no upper bound” (full p.u. allowed) and lets the candidate be freely chosen by the optimisation.

Variable electric transmission line TTC forward and backward (optional files)

A description of the data included in the files oT_Data_VariableTTCFrw.csv and oT_Data_VariableTTCBck.csv follows:

Identifiers			Header			Description
Period	Scenario	LoadLevel	Initial node	Final node	Circuit	Maximum TTC forward (backward) of an electric transmission line by load level	MW

Not all the electric transmission lines must be defined as columns of these files, only those with values different from 0.

This information can be used to consider the transmission line’s weather-dependent maximum capacity.

To force the flow of a transmission line to be 0, a small value (e.g., 0.1 MW) strictly >0, but not 0 (in which case the value will be ignored), must be introduced. Suppose the user introduces a minimum transmission line capacity value that is greater than the maximum transmission line capacity value. In that case, the model will adjust the minimum transmission line capacity value to match the maximum.

If you want to force the flow of a transmission line to be equal to a value, introduce the same value (with opposite sign) in both files (e.g., 125 MW in oT_Data_VariableTTCFrw.csv and -125 MW in oT_Data_VariableTTCBck.csv) or vice versa.

Internally, all the values below 1e-5 times the maximum system demand of each area will be converted into 0 by the model.

If the variables TTCFrw and TTBck are both very small (e.g., 0.000001) for any time step, they are set to 0, and the line flow is forced to be 0, i.e., the line is switched off.

Node location

At least two different nodes must be defined.

A description of the data included in the file oT_Data_NodeLocation.csv follows:

Identifier	Header	Description
Node	Latitude	Node latitude	º
Node	Longitude	Node longitude	º

Hydropower System Input Data

These input files are introduced explicitly to allow a representation of the hydropower system based on volume and water inflow data, considering the water stream topology (hydro cascade basins). If they are unavailable, the model runs with an energy-based representation of the hydropower system.

Dictionaries. Sets

The dictionaries include all the possible elements of the corresponding sets in the optimization problem. You can’t use non-English characters (e.g., ó, º)

File	Description
oT_Dict_Reservoir.csv	Reservoirs

The information contained in these input files determines the topology of the hydro basins and how water flows along the different hydropower and pumped-hydro power plants and reservoirs. These relations follow the water downstream direction.

File	Dictionary	Description
oT_Dict_ReservoirToHydro.csv	ReservoirToHydro	Reservoir upstream of hydropower plant (i.e., hydro takes the water from the reservoir)
oT_Dict_HydroToReservoir.csv	HydroToReservoir	Hydropower plant upstream of reservoir (i.e., hydro releases the water to the reservoir)
oT_Dict_ReservoirToPumpedHydro.csv	ReservoirToPumpedHydro	Reservoir upstream of pumped-hydro power plant (i.e., pumped-hydro pumps from the reservoir)
oT_Dict_PumpedHydroToReservoir.csv	PumpedHydroToReservoir	Pumped-hydro power plant upstream of reservoir (i.e., pumped-hydro pumps to the reservoir)
oT_Dict_ReservoirToReservoir.csv	ReservoirToReservoir	Reservoir upstream of reservoir (i.e., reservoir one spills the water to reservoir two)

Natural water inflows

A description of the data included in the file oT_Data_HydroInflows.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Reservoir	Natural water inflows by load level	m3/s

All the reservoirs must be defined as columns in these files.

If you have daily natural water inflow data, just input the daily amount during the first hour of every day to see if the reservoir has daily or weekly storage capacity.

Internally, all the values below 1e-5 times the maximum system demand of each area will be converted into 0 by the model.

Natural water outflows

A description of the data included in the file oT_Data_HydroOutflows.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Reservoir	Water outflows by load level (e.g., for irrigation	m3/s

All the reservoirs must be defined as columns in these files.

These water outflows can be used to represent the water outflows for irrigation.

If you have hourly/daily/weekly/monthly/yearly water outflow data, you can just input the daily/weekly/monthly/yearly amount at the first hour of every day/week/month/year.

Internally, all the values below 1e-5 times the maximum system demand of each area will be converted into 0 by the model.

Reservoir

A description of the data included in the file oT_Data_Reservoir.csv follows:

Header	Description
StorageType	Reservoir storage type based on reservoir storage capacity (hourly, daily, weekly, monthly, yearly)	Hourly/Daily/Weekly/Monthly/Yearly
OutflowsType	Water outflows type based on the water extracted from the reservoir (daily, weekly, monthly, yearly)	Daily/Weekly/Monthly/Yearly
InitialStorage	Initial volume stored at the first instant of the time scope	hm3
MaximumStorage	Maximum volume that the hydro reservoir can store	hm3
MinimumStorage	Minimum volume that the hydro reservoir can store	hm3
BinaryInvestment	Binary reservoir investment decision	Yes/No
FixedInvestmentCost	Overnight investment (capital -CAPEX- and fixed O&M -FOM-) cost	M€
FixedChargeRate	Fixed-charge rate to annualize the overnight investment cost	p.u.
InitialPeriod	Initial period (year) when the unit is installed or can be installed, if candidate	Year
FinalPeriod	Final period (year) when the unit is installed or can be installed, if candidate	Year

The model always considers a month of 672 hours, i.e., 4 weeks, not calendar months. The model assumes a year of 8736 hours, i.e., 52 weeks, not calendar years.

Daily storage type means the ESS inventory is assessed every time step. For the daily storage type, it is evaluated at the end of every hour; for the weekly storage type, it is assessed at the end of every day; for the monthly storage type, it is evaluated at the end of every week; and yearly storage type is assessed at the end of every month. Outflows type represents the interval when the energy extracted from the storage must be satisfied (for daily outflows type at the end of every day, i.e., the energy consumed must equal the sum of outflows for every day). The storage cycle is the minimum between the inventory assessment period (defined by the storage type), the outflows period (determined by the outflows type), and the energy period (defined by the energy type) (only if outflows or energy power values have been introduced). It can be one time step, day, week, and month, but it can’t exceed the stage duration. For example, if the stage lasts 168 hours the storage cycle can only be hourly or daily.

The initial reservoir volume is also fixed at the beginning and end of each stage, only if the initial volume lies between the reservoir storage limits. For example, the initial volume is set for the hour 8736 in case of a single stage or for the hours 4368 and 4369 (end of the first stage and beginning of the second stage) in case of two stages, each with 4368 hours.

Variable maximum and minimum reservoir volume

A description of the data included in the files oT_Data_VariableMaxVolume.csv and oT_Data_VariableMinVolume.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Reservoir	Maximum (minimum) reservoir volume by load level	hm3

Not all the reservoirs must be defined as columns of these files, only those with values different from 0.

It can be used also for upper-bounding and/or lower-bounding the volume of any reservoir. If the user introduces a maximum volume value that is lower than the minimum volume value, the model will adjust the minimum volume value to match the maximum.

For example, these data can be used to define the operating guide (rule) curves for the hydro reservoirs.

Hydrogen System Input Data

These input files are specifically introduced to allow a representation of the hydrogen energy vector to supply the hydrogen demand produced with electricity or by any other means through the hydrogen network. The hydro data are expressed in tH2. However, a very simple conversion can be applied to convert them into MWh by multiplying the tH2 values by 33.33 MWh/tH2 (the lower heating value of hydrogen). Suppose you want to represent the hydrogen demand in MWh instead of tH2. In that case, they can input the hydrogen demand in MWh in the file oT_Data_DemandHydrogen.csv and then convert it into tH2 by dividing the MWh values by 33.33 MWh/tH2.

If the hydrogen is only produced from electricity and there is no hydrogen flows among nodes, the hydrogen demand can be represented by the energy outflows associated with the unit (i.e., electrolyzer) and no need to consider these hydrogen demand and network files.

File	Description
oT_Data_DemandHydrogen.csv	Hydrogen demand
oT_Data_NetworkHydrogen.csv	Hydrogen pipeline network data

Hydrogen demand

A description of the data included in the file oT_Data_DemandHydrogen.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Node	Hydrogen demand of the node for each load level	tH2/h

Internally, all the values below if positive demand (or above if negative demand) 1e-5 times the maximum system demand of each area will be converted into 0 by the model.

Hydrogen transmission pipeline network

A description of the circuit (initial node, final node, circuit) data included in the file oT_Data_NetworkHydrogen.csv follows:

Header	Description
InitialPeriod	Initial period (year) when the unit is installed or can be installed, if candidate	Year
FinalPeriod	Final period (year) when the unit is installed or can be installed, if candidate	Year
Length	Pipeline length (only used for reporting purposes). If not defined, computed as 1.1 times the geographical distance	km
TTC	Total transfer capacity (maximum permissible hydrogen flow) in forward direction. Static pipeline rating	tH2
TTCBck	Total transfer capacity (maximum permissible hydrogen flow) in backward direction. Static pipeline rating	tH2
SecurityFactor	Security factor to consider approximately N-1 contingencies. NTC = TTC x SecurityFactor All the security factors can’t be 0. Otherwise, there is no network.	p.u.
FixedInvestmentCost	Overnight investment (capital -CAPEX- and fixed O&M -FOM-) cost	M€
FixedChargeRate	Fixed-charge rate to annualize the overnight investment cost	p.u.
BinaryInvestment	Binary pipeline investment decision	Yes/No
InvestmentLo	Lower bound of investment decision	p.u.
InvestmentUp	Upper bound of investment decision	p.u.

The initial and final nodes are where the transmission line starts and ends. They must be different.

If there is no data for TTCBck, i.e., TTCBck is left empty or is equal to 0, the TTC substitutes it in the code. Internally, all the TTC and TTCBck values below 1e-5 times the maximum system demand of each area will be converted into 0 by the model.

Those pipelines with fixed costs>0 are considered candidates and can be installed.

If the lower and upper bounds of investment decisions are very close (with a difference <1e-4) to 0 or 1, they are converted into 0 and 1. To forbid investment on a candidate pipeline, set InvestmentUp to 1e-5: it falls below the snap threshold and is internally converted to 0. A blank cell or 0 in this column is interpreted as “no upper bound” (full p.u. allowed) and lets the candidate be freely chosen by the optimisation.

Heat System Input Data

These input files are specifically introduced to allow a representation of the heat energy vector to supply heat demand produced with electricity or with any fuel through the heat network. Suppose the heat is only produced from electricity without heat transfer among nodes. In that case, the heat demand can be represented by the energy outflows associated with the unit (i.e., heat pump or electric boiler).

File	Description
oT_Data_ReserveMarginHeat.csv	Heat reserve margin
oT_Data_DemandHeat.csv	Heat demand
oT_Data_NetworkHeat.csv	Heat pipeline network data

Heat adequacy reserve margin

The adequacy reserve margin for heating is the ratio between the available capacity and the maximum demand. It is modeled as the adequacy reserve margin for electricity, considering the units’ heat demand and heat capacity. A description of the data included in the file oT_Data_ReserveMarginHeat.csv follows:

Identifiers		Header	Description
Period	Area	ReserveMargin	Minimum heat adequacy reserve margin for each period and area	p.u.

This parameter is only used for system heating generation expansion, not for the system operation. If no value is introduced for an area, the reserve margin is considered 0.

Heat demand

A description of the data included in the file oT_Data_DemandHeat.csv follows:

Identifiers			Header	Description
Period	Scenario	LoadLevel	Node	Heat demand of the node for each load level	MW

Internally, if positive demand (or above if negative demand) is 1e-5 times the maximum system demand of each area, all the values below will be converted into 0 by the model.

Heat transmission pipeline network

A description of the circuit (initial node, final node, circuit) data included in the file oT_Data_NetworkHeat.csv follows:

Header	Description
InitialPeriod	Initial period (year) when the unit is installed or can be installed, if candidate	Year
FinalPeriod	Final period (year) when the unit is installed or can be installed, if the candidate	Year
Length	Pipeline length (only used for reporting purposes). If not defined, computed as 1.1 times the geographical distance	km
TTC	Total transfer capacity (maximum permissible heat flow) in forward direction. Static pipeline rating	MW
TTCBck	Total transfer capacity (maximum permissible heat flow) in backward direction. Static pipeline rating	MW
SecurityFactor	Security factor to consider approximately N-1 contingencies. NTC = TTC x SecurityFactor All the security factors can’t be 0. Otherwise, there is no network.	p.u.
FixedInvestmentCost	Overnight investment (capital -CAPEX- and fixed O&M -FOM-) cost	M€
FixedChargeRate	Fixed-charge rate to annualize the overnight investment cost	p.u.
BinaryInvestment	Binary pipeline investment decision	Yes/No
InvestmentLo	Lower bound of investment decision	p.u.
InvestmentUp	Upper bound of investment decision	p.u.

The initial and final nodes are where the transmission line starts and ends. They must be different.

If there is no data for TTCBck, i.e., TTCBck is left empty or is equal to 0, the TTC substitutes it in the code. Internally, all the TTC and TTCBck values below 1e-5 times the maximum system demand of each area will be converted into 0 by the model.

Those pipelines with fixed costs>0 are considered candidates and can be installed.

If the lower and upper bounds of investment decisions are very close (with a difference <1e-4) to 0 or 1, they are converted into 0 and 1. To forbid investment on a candidate pipeline, set InvestmentUp to 1e-5: it falls below the snap threshold and is internally converted to 0. A blank cell or 0 in this column is interpreted as “no upper bound” (full p.u. allowed) and lets the candidate be freely chosen by the optimisation.

Flow-Based Market Coupling Method

This input file is introduced explicitly to allow the flow-based market coupling method. If they are not available, the model runs with the DCOPF method.

File	Description
oT_Data_VariablePTDF.csv	Power transfer distribution factors (PTDF)

Variable power transfer distribution factors

A description of the data included in the file oT_Data_VariablePTDF.csv follows:

Identifiers			Header				Description
Period	Scenario	LoadLevel	Initial node	Final node	Circuit	Node	Power transfer distribution factors by load level	p.u.

Not all the transmission lines must be defined as columns of these files, only those with values different from 0.