urbs
Parameter | Unit | Description |
---|---|---|
General Technical Parameters | ||
w | _ | Fraction of 1 year of modeled timesteps |
Δt | h | Timestep Size |
W | a | Weight of last support timeframe |
Commodity Technical Parameters | ||
dyvct | MWh | Demand for Commodity |
syvct | _ | Intermittent Supply Capacity Factor |
MW | Maximum Stock Supply Limit Per Hour | |
MWh | Maximum Annual Stock Supply Limit Per Vertex | |
t/h | Maximum Environmental Output Per Hour | |
t | Maximum Annual Environmental Output | |
MW | Maximum Sell Limit Per Hour | |
MWh | Maximum Annual Sell Limit | |
MW | Maximum Buy Limit Per Hour | |
MWh | Maximum Annual Buy Limit | |
t | Maximum Global Annual CO2 Emission Limit | |
t | CO2 Emission Budget for modeling horizon | |
Process Technical Parameters | ||
MW | Process Capacity Lower Bound | |
Kvp | MW | Process Capacity Installed |
MW | Process Capacity Upper Bound | |
Tvp | MW | Remaining lifetime of installed processes |
1/h | Process Maximal Power Gradient (relative) | |
_ | Process Minimum Part Load Fraction | |
fyvptout | _ | Process Output Ratio multiplyer |
rypcin | _ | Process Input Ratio |
_ | Process Partial Input Ratio | |
_ | Process Partial Output Ratio | |
rypcout | _ | Process Output Ratio |
Storage Technical Parameters | ||
Iyvs | _ | Initial and Final State of Charge |
eyvsin | _ | Storage Efficiency During Charge |
eyvsout | _ | Storage Efficiency During Discharge |
dyvs | 1/h | Storage Self-discharge Per Hour |
MWh | Storage Capacity Lower Bound | |
Kyvsc | MWh | Storage Capacity Installed |
MWh | Storage Capacity Upper Bound | |
MW | Storage Power Lower Bound | |
Kyvsp | MW | Storage Power Installed |
MW | Storage Power Upper Bound | |
Tvs | MW | Remaining lifetime of installed storages |
kyvsE/P | h | Storage Energy to Power Ratio |
Transmission Technical Parameters | ||
eyaf | _ | Transmission Efficiency |
MW | Tranmission Capacity Lower Bound | |
Kyaf | MW | Tranmission Capacity Installed |
MW | Tranmission Capacity Upper Bound | |
Taf | MW | Remaining lifetime of installed transmission |
Demand Side Management Parameters | ||
eyvc | _ | DSM Efficiency |
yyvc | _ | DSM Delay Time |
oyvc | _ | DSM Recovery Time |
MW | DSM Maximal Upshift Per Hour | |
MW | DSM Maximal Downshift Per Hour |
Weight, w, weight
: The parameter w helps to scale variable costs and emissions from the length of simulation, that the energy system model is being observed, to an annual result. This parameter represents the fraction of a year (8760 hours) of the observed time span. The observed time span is calculated by the product of number of time steps of the set T and the time step duration. In script model.py
this parameter is defined by the model parameter weight
and initialized by the following code fragment: :
m.weight = pyomo.Param(
initialize=float(8760) / (len(m.tm) * dt),
doc='Pre-factor for variable costs and emissions for an annual result')
Timestep Duration, Δt, dt
: The parameter Δt represents the duration between two sequential timesteps tx and tx + 1. This is calculated by the subtraction of smaller one from the bigger of the two sequential timesteps Δt = tx + 1 − tx. This parameter is the unit of time for the optimization model, is expressed in the unit h and by default the value is set to 1
. In script model.py
this parameter is defined by the model parameter dt
and initialized by the following code fragment: :
m.dt = pyomo.Param(
initialize=dt,
doc='Time step duration (in hours), default: 1')
The user can set the paramteter in script runme.py
in the line: :
dt = 1 # length of each time step (unit: hours)
Weight of last modeled support timeframe, W, m.global_prop.loc[(min(m.stf), 'Cost budget'), 'value']
: This parameter specifies how long the time interval represented by the last support timeframe is. The unit of this parameter is years. By extension it also specifies the end of the modeling horizon. The parameter is set in the spreadsheet corresponding to the last support timeframe in worksheet "Global" in the line denoted "Weight" in the column titled "value".
Demand for Commodity, dyvct, m.demand_dict[(stf, sit, com)][tm]
: The parameter represents the energy amount of a demand commodity tuple cyvq required at a timestep t (
Intermittent Supply Capacity Factor, syvct, m.supim_dict[(stf, sit, coin)][tm]
: The parameter syvct represents the normalized availability of a supply intermittent commodity c (∀c ∈ Csup) in a support timeframe y and site v at a timestep t. In other words this parameter gives the ratio of current available energy amount to maximum potential energy amount of a supply intermittent commodity. This data is to be provided by the user and to be entered in the spreadsheet corresponding to the support timeframe. The related section for this parameter in the spreadsheet can be found under the "SupIm" sheet. Here each row represents another timestep t and each column represent a commodity tuple cvq. Rows are named after the timestep number n of timesteps tn. Columns are named after the combination of site name v and commodity name c, in this respective order and separated by a period(.). For example (Mid.Elec) represents the commodity Elec in site Mid. Commodity Type q is omitted in column declarations, because every commodity of this parameter has to be from commodity type SupIm in any case.
Maximum Stock Supply Limit Per Hour, m.commodity_dict['maxperhour'][(stf, sit, com, com_type)]
: The parameter Commodity
sheet. Here each row represents another commodity tuple cyvq and the column with the header label "maxperhour" represents the parameter
Maximum Annual Stock Supply Limit Per Vertex, m.commodity_dict['max'][(stf, sit, com, com_type)]
: The parameter Commodity
sheet. Here each row represents another commodity tuple cyvq and the column with the header label "max" represents the parameter
Maximum Environmental Output Per Hour, m.commodity_dict['maxperhour'][(stf, sit, com, com_type)]
: The parameter Commodity
sheet. Here each row represents another commodity tuple cyvq and the column with the header label "maxperhour" represents the parameter
Maximum Annual Environmental Output, m.commodity_dict['max'][(stf, sit, com, com_type)]
: The parameter Commodity
sheet. Here each row represents another commodity tuple cyvq and the column with the header label "max" represents the parameter
Maximum Sell Limit Per Hour, m.commodity_dict['maxperhour'][(stf, sit, com, com_type)]
: The parameter Commodity
sheet. Here each row represents another commodity tuple cyvq and the column with the header label "maxperhour" represents the parameter
Maximum Annual Sell Limit, m.commodity_dict['max'][(stf, sit, com, com_type)]
: The parameter Commodity
sheet. Here each row represents another commodity tuple cyvq and the column of sell with the header label "max" represents the parameter
Maximum Buy Limit Per Hour, m.commodity_dict['maxperhour'][(stf, sit, com, com_type)]
: The parameter Commodity
sheet. Here each row represents another commodity tuple cyvq and the column with the header label "maxperhour" represents the parameter
Maximum Annual Buy Limit, m.commodity_dict['max'][(stf, sit, com, com_type)]
: The parameter Commodity
sheet. Here each row represents another commodity tuple cyvq and the column with the header label "max" represents the parameter
Maximum Global Annual CO2 Annual Emission Limit, m.global_prop.loc[stf, 'CO2 limit']['value']
: The parameter
CO2** emission budget Total Emission budget, m.global_prop.loc[min(m.stf), 'CO2 budget']['value']
: The parameter
Process Capacity Lower Bound, m.process_dict['cap-lo'][stf, sit, pro]
: The parameter
Process Capacity Installed, Kvp, m.process_dict['inst-cap'][min(m.stf), sit, pro]
: The parameter Kvp represents the amount of power output capacity of a process p in a site v, that is already installed to the energy system at the beginning of the modeling period. The unit of this parameter is MW. The related section for this parameter can be found in the spreadsheet corresponding to the first support timeframe under the "Process" sheet. Here each row represents another process p in a site v and the column with the header label "inst-cap" represents the parameters Kvp belonging to the corresponding process p and site v combinations.
Process Capacity Upper Bound, m.process_dict['cap-up'][stf, sit, pro]
: The parameter
Remaining lifetime of installed processes, Tvp, m.process.loc[(min(m.stf), sit, pro), 'lifetime']
: The parameter Tvp represents the remaining lifetime of already installed units. It is used to determine the set m.inst_pro_tuples, i.e. to identify for which support timeframes the installed unit can still be used.
Process Maximal Gradient, m.process_dict['max-grad'][(stf, sit, pro)]
: The parameter
Process Minimum Part Load Fraction, m.process_dict['min-fraction'][(stf, sit, pro)]
: The parameter
Process Output Ratio multiplyer, fyvptout, m.eff_factor_dict[(stf, sit, pro)]
: The parameter time series fyvptout allows for a time dependent modification of process outputs and by extension of the efficiency of a process p in site v and support timeframe y. It can be used, e.g., to model temperature dependent efficiencies of processes or to include scheduled maintenance intervals. In the spreadsheet corresponding to the support timeframe this timeseries is set in worksheet "TimeVarEff". Here each row represents another timestep t and each column represent a process tuple pyv. Rows are named after the timestep number n of timesteps tn. Columns are named after the combination of site name v and commodity name and process name p respecting the order and seperated by a period(.). For example (Mid, Lignite plant) represents the process Lignite plant in site Mid. Note that the output of environmental commodity outputs are not manipulated by this factor as it is typically linked to an input commodity as , e.g., CO2 output is linked to a fossil input.
Process Input Ratio, rypcin, m.r_in_dict[(stf, pro, co)]
: The parameter rypcin represents the ratio of the input amount of a commodity c in a process p and support timeframe y, relative to the process throughput at a given timestep. The related section for this parameter in the spreadsheet corresponding to the support timeframe can be found under the "Process-Commodity" sheet. Here each row represents another commodity c that either goes in to or comes out of a process p. The column with the header label "ratio" represents the parameters rypcin of the corresponding process p and commodity c if the latter is an input commodity.
Process Partial Input Ratio, m.r_in_min_fraction[stf, pro, coin]
: The parameter
Process Output Ratio, rypcout, m.r_out_dict[(stf, pro, co)]
: The parameter rypcout represents the ratio of the output amount of a commodity c in a process p in support timeframe y, relative to the process throughput at a given timestep. The related section for this parameter in the spreadsheet corresponding to the support timeframe can be found under the "Process-Commodity" sheet. Here each row represents another commodity c that either goes in to or comes out of a process p. The column with the header label "ratio" represents the parameters of the corresponding process p and commodity c if the latter is an output commodity.
Process Partial Output Ratio, m.r_out_min_fraction[stf, pro, coo]
: The parameter
Process input and output ratios are, in general, used for unit conversion between the different commodities.
Since all costs and capacity constraints take the process throughput τyvpt as the reference, it is reasonable to assign an in- or output ratio of "1" to at least one commodity. The flow of this commodity then tracks the throughput and can be used as a reference. All other values of in-and output ratios can then be adjusted by scaling them by an appropriate factor to the reference commodity flow.
Initial and Final State of Charge (relative), Iyvs, m.storage_dict['init'][(stf, sit, sto, com)]
: The parameter Iyvs represents the initial state of charge of a storage s in a site v and support timeframe y. If this value is left unspecified, the initial state of charge is variable. The initial and final value are set as identical in each modeled support timeframe to avoid windfall profits through emptying of a storage. The value of this parameter is expressed as a normalized percentage, where "1" represents a fully loaded storage and "0" represents an empty storage. The related section for this parameter in the spreadsheet corresponding to the support timeframe can be found under the "Storage" sheet. Here each row represents a storage technology s in a site v that stores a commodity c. The column with the header label "init" represents the parameters for corresponding storage s, site v, commodity c combinations. When no initial value is to be set this cell can be left empty.
Storage Efficiency During Charge, eyvsin, m.storage_dict['eff-in'][(stf, sit, sto, com)]
: The parameter eyvsin represents the charging efficiency of a storage s in a site v and support timeframe y that stores a commodity c. The charging efficiency shows, how much of a desired energy and accordingly power can be successfully stored into a storage. The value of this parameter is expressed as a normalized percentage, where "1" represents a charging without energy losses. The related section for this parameter in the spreadsheet corresponding to the support timeframe can be found under the "Storage" sheet. Here each row represents a storage technology s in a site v that stores a commodity c. The column with the header label "eff-in" represents the parameters eyvsin for corresponding storage tuples.
Storage Efficiency During discharge, eyvsout, m.storage_dict['eff-out'][(stf, sit, sto, com)]
: The parameter eyvsout represents the discharging efficiency of a storage s in a site v and support timeframe y that stores a commodity c. The discharging efficiency shows, how much of a desired energy and accordingly power can be successfully released from a storage. The value of this parameter is expressed as a normalized percentage, where "1" represents a discharging without energy losses. The related section for this parameter in the spreadsheet corresponding to the support timeframe can be found under the "Storage" sheet. Here each row represents a storage technology s in a site v that stores a commodity c. The column with the header label "eff-out" represents the parameters eyvsout for corresponding storage tuples.
Storage Self-discharge Per Hour, dyvs, m.storage_dict['discharge'][(stf, sit, sto, com)]
: The parameter dvs represents the fraction of the energy content within a storage which is lost due to self-discharge per hour. It introduces an exponential decay of a given storage state if no charging/discharging takes place. The unit of this parameter is 1/h. The related section for this parameter in the spreadsheet corresponding to the support timeframe can be found under the "Storage" sheet. Here each row represents a storage technology s in a site v that stores a commodity c. The column with the header label "discharge" represents the parameters dyvs for corresponding storage tuples.
Storage Capacity Lower Bound, m.storage_dict['cap-lo-c'][(stf, sit, sto, com)]
: The parameter
Storage Capacity Installed, Kvsc, m.storage_dict['inst-cap-c'][(min(m.stf), sit, sto, com)]]
: The parameter Kvsc represents the amount of energy content capacity of a storage s storing commodity c in a site v and support timeframe y, that is already installed to the energy system at the beginning of the model horizon. The unit of this parameter is MWh. The related section for this parameter in the spreadsheet corresponding to the first support timeframe can be found under the "Storage" sheet. Here each row represents a storage technology s in a site v that stores a commodity c. The column with the header label "inst-cap-c" represents the parameters Kvsc for corresponding storage tuples.
Storage Capacity Upper Bound, m.storage_dict['cap-up-c'][(stf, sit, sto, com)]
: The parameter
Storage Power Lower Bound, m.storage_dict['cap-lo-p'][(stf, sit, sto, com)]
: The parameter
Storage Power Installed, Kvsp, m.storage_dict['inst-cap-p'][(min(m.stf), sit, sto, com)]]
: The parameter Kvsp represents the amount of charging/discharging power of a storage s storing commodity c in a site v and support timeframe y, that is already installed to the energy system at the beginning of the model horizon. The unit of this parameter is MW. The related section for this parameter in the spreadsheet corresponding to the first support timeframe can be found under the "Storage" sheet. Here each row represents a storage technology s in a site v that stores a commodity c. The column with the header label "inst-cap-p" represents the parameters Kvsp for corresponding storage tuples.
Storage Power Upper Bound, m.storage_dict['cap-up-p'][(stf, sit, sto, com)]
: The parameter
Remaining lifetime of installed storages, Tvs, m.storage.loc[(min(m.stf), sit, pro), 'lifetime']
: The parameter Tvs represents the remaining lifetime of already installed units. It is used to determine the set m.inst_sto_tuples, i.e. to identify for which support timeframes the installed units can still be used.
Storage Energy to Power Ratio, kyvsE/P, m.storage_dict['ep-ratio'][(stf, sit, sto, com)]
: The parameter kyvsE/P represents the linear ratio between the energy and power capacities of a storage s storing a commodity c in a site v in support timeframe y. The unit of this parameter is hours. The related section for this parameter in the spreadsheet corresponding to the support timeframe can be found under the "Storage" sheet. Here each row represents a storage technology s in a site v that stores a commodity c. The column with the header label "ep-ratio" represents the parameters kyvsE/P for corresponding storage tuples. If there is no desired set ratio for the storage energy and power capacities (which means the storage energy and power capacities can be sized independently from each other), this cell can be left empty.
Transmission Efficiency, eyaf, m.transmission_dict['eff'][(stf, sin, sout, tra, com)]
: The parameter eyaf represents the energy efficiency of a transmission f that transfers a commodity c through an arc a in support timeframe y. Here an arc a defines the connection line from an origin site vout to a destination site vin. The ratio of the output energy amount to input energy amount, gives the energy efficiency of a transmission process. The related section for this parameter in the spreadsheet corresponding to the support timeframe can be found under the "Transmission" sheet. Here each row represents another combination of transmission f and arc a. The column with the header label "eff" represents the parameters eyaf of the corresponding transmission tuples.
Transmission Capacity Lower Bound, m.transmission_dict['cap-lo'][(stf, sin, sout, tra, com)]
: The parameter
Transmission Capacity Installed, Kaf, m.transmission_dict['inst-cap'][(min(m.stf), sin, sout, tra, com)]
: The parameter Kaf represents the amount of power output capacity of a transmission f transferring a commodity c through an arc a, that is already installed to the energy system at the beginning of the modeling horizon. The unit of this parameter is MW. The related section for this parameter in the spreadsheet corresponding to the first support timeframe can be found under the "Transmission" sheet. Here each row represents another transmission f, arc a combination. The column with the header label "inst-cap" represents the parameters Kaf of the transmission tuples.
Transmission Capacity Upper Bound, m.transmission_dict['cap-up'][(stf, sin, sout, tra, com)]
: The parameter
Remaining lifetime of installed transmission, Taf, m.transmission.loc[(min(m.stf), sitin, sitout, tra, com), 'lifetime']
: The parameter Taf represents the remaining lifetime of already installed units. It is used to determine the set m.inst_tra_tuples, i.e. to identify for which support timeframes the installed units can still be used.
DSM Efficiency, eyvc, m.dsm_dict['eff'][(stf, sit, com)]
: The parameter eyvc represents the efficiency of the DSM process, i.e., the fraction of DSM upshift that is benefiting the system via the corresponding DSM downshifts of demand commodity c in site v and support timeframe y. The parameter is given as a fraction with "1" meaning a perfect recovery of the DSM upshift. The related section for this parameter in the spreadsheet corresponding to the support timeframe can be found under the "DSM" sheet. Here each row represents another DSM potential for demand commodity c in site v. The column with the header label "eff" represents the parameters eyvc of the corresponding DSM tuples.
DSM Delay Time, yyvc, m.dsm_dict['delay'][(stf, sit, com)]
: The delay time yyvc restricts how long the time difference between an upshift and its corresponding downshifts may be for demand commodity c in site v and support timeframe y. The parameter is given in h. The related section for this parameter in the spreadsheet corresponding to the support timeframe can be found under the "DSM" sheet. Here each row represents another DSM potential for demand commodity c in site v. The column with the header label "delay" represents the parameters yyvc of the corresponding DSM tuples.
DSM Recovery Time, oyvc, m.dsm_dict['recov'][(stf, sit, com)]
: The recovery time oyvc prevents the DSM system to continuously shift demand. During the recovery time, all upshifts of demand commodity c in site v and support timeframe y may not exceed the product of the delay time and the maximal upshift capacity. The parameter is given in h. The related section for this parameter in the spreadsheet corresponding to the support timeframe can be found under the "DSM" sheet. Here each row represents another DSM potential for demand commodity c in site v. The column with the header label "recov" represents the parameters oyvc of the corresponding DSM tuples. If no limitation via this parameter is desired it has to be set to values lower than the delay time yyvc.
DSM Maximal Upshift Per Hour, m.dsm_dict['cap-max-up'][(stf, sit, com)]
: The DSM upshift capacity
DSM Maximal Downshift Per Hour, m.dsm_dict['cap-max-do'][(stf, sit, com)]
: The DSM downshift capacity