# Techno-data¶

The techno-data includes the techno-economic characteristics of each technology such as capital, fixed and variable cost, lifetime, utilisation factor. The techno-data should follow the structure reported in the table. The column order is not important and additional input data can alsobe read in this format. In the table, the electric boiler used in households is taken as an example for a generic region, region1.

Techno-data

ProcessName

RegionName

Time

Level

cap_par

cap_exp

fix_par

resBoilerElectric

region1

2010

fixed

3.81

1.00

0.38

resBoilerElectric

region1

2030

fixed

3.81

1.00

0.38

ProcessName

represents the technology ID and needs to be consistent across all the data inputs

RegionName

represents the region ID and needs to be consistent across all the data inputs

Time

represents the period of the simulation to which the value applies; it needs to contain at least the base year of the simulation

Level

characterises either a fixed or a flexible input type

cap_par, cap_exp

are used in the capital cost estimation. Capital costs are calculated as:

$\text{CAPEX} = \text{cap\_par} * \text{(Capacity)}^\text{cap\_exp}$

where the parameter cap_par is estimated at a selected reference size (i.e. Capref), such as:

$\text{cap\_par} = \left( \frac{\text{CAPEXref}}{\text{Capref}} \right)^{\text{cap\_exp}}$

Capref is decided by the modeller before filling the input data files.

This allows the model to take into account economies of scale. ie. As Capacity increases, the price of the technology decreases. This does not include technological learning parameters, where prices may come down due to learning.

fix_par, fix_exp

are used in the fixed cost estimation. Fixed costs are calculated as:

$\text{FOM} = \text{fix\_par} * (\text{Capacity})^\text{fix\_exp}$

where the parameter fix_par is estimated at a selected reference size (i.e. Capref), such as:

$\text{fix\_par} = \left( \frac{\text{FOMref}}{\text{Capref}} \right)^{\text{fix\_exp}}$

Capref is decided by the modeller before filling the input data files.

var_par, var_exp

are used in the variable costs estimation. These variable costs are capacity dependent Variable costs are calculated as:

$\text{VAREX} = \text{cap\_par} * \text{(Capacity)}^{\text{cap\_exp}}$

where the parameter var_par is estimated at a selected reference size (i.e. Capref), such as:

$\text{var\_par} = \left( \frac{\text{VARref}}{\text{Capref}} \right)^{\text{var\_exp}}$

Capref is decided by the modeller before filling the input data files.

represents the maximum addition of installed capacity per technology, per year in a period, per region.

MaxCapacityGrowth

represents the percentage growth per year based on the available stock in a year, per region and technology.

TotalCapacityLimit

represents the total capacity limit per technology, region and year.

TechnicalLife

represents the number of years that a technology operates before it is decommissioned.

UtilizationFactor

represents the maximum actual output of the technology in a year, divided by the theoretical maximum output if the technology were operating at full capacity for the whole year.

ScalingSize

represents the minimum size of a technology to be installed.

efficiency

is calculated as the ratio between the total output commodities and the input commodities.

Type

defines the type of a technology. This variable is used for the search space in the agents csv file. It allows for the agents to filter for technologies of a similar type, for example.

Fuel

defines the fuel used by a technology.

EndUse

defines the end use of a technology.

InterestRate

is the technology interest rate. This is used for the interest used in the discount rate.

Agent_0, …, Agent_N

represent the allocation of the initial capacity to the each agent.

The input data has to be provided for the base year. Additional years within the time framework of the overall simulation can be defined. In this case, MUSE would interpolate the values between the provided periods and assume a constant value afterwards.