9.3.3. 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: cost inputs

ProcessName	RegionName	Time	cap_par	cap_exp	fix_par	…
resBoilerElectric	region1	2010	3.81	1.00	0.38	…
resBoilerElectric	region1	2030	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

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 a reference size for the cost estimate 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 capacity (i.e. CapRef), such as:

\[\text{fix$\_$par}= \frac{\text{FOMref}}{(\text{CapRef})^\text{fix$\_$exp}}\]

CapRef is a reference size for the cost estimate 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 production dependent Variable costs are calculated as:

\[\text{VAREX} = \text{var$\_$par} * \text{(Production)}^{\text{var$\_$exp}}\]

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

\[\text{var$\_$par}= \frac{\text{VARref}}{(\text{ProductionRef})^\text{var$\_$exp}}\]

ProductionRef is the production of a reference capacity (CapRef) for the cost estimate decided by the modeller before filling the input data files.

Growth constraints (optional)

MaxCapacityAddition

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

MaxCapacityGrowth

represents the fraction growth per year based on the available stock in a year, per region and technology. To allow growth to be initiated, a seed value must be specified (see GrowthSeed below).

TotalCapacityLimit

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

Techno-data: growth constraints

ProcessName	RegionName	MaxCapacityAddition	MaxCapacityGrowth	TotalCapacityLimit
resBoilerElectric	region1	10	0.2	100

In this example, MaxCapacityAddition, MaxCapacityGrowth and TotalCapacityLimit equal to 10 PJ, 0.2 (corresponding to 20 %), and 100 PJ. Assuming a 5-year time step:

• MaxCapacityAddition restricts new capacity which can be installed over the investment period to 10 * 5 = 50 PJ.

• MaxCapacityGrowth restricts capacity growth to 20 % per year (\(\approx\) 149 % over 5 years). The investment limit will depend on the existing capacity and the decommissioning profile. Assuming that 7.7 PJ of resBoilerElectric is available in the current year, and that 4.9 PJ of resBoilerElectric is already commissioned for the investment year, then the constraint applies as follows: 7.7 * (1 + 0.2)⁵ - 4.9 = 14.3 PJ. Also see the GrowthSeed parameter below.

• TotalCapacityLimit will restrict new addition to 100 - 4.9 = 95.1 PJ (so that total capacity in the investment year will not exceed 100 PJ).

• Overall, the most restrictive constraint will apply, which in this case is 14.3 PJ.

Growth constraints are applied for each single agent in a multi-agent simulation. When only one agent is present, the growth constraints apply individually to the “New” and “Retrofit” agent, when present.

If any of the three parameters are not provided in the technodata file, that particular constraint is not applied.

GrowthSeed (optional, default = 1)

applies a lower-bound on the initial capacity value used in the MaxCapacityGrowth calculation, allowing growth to initiate when capacity is low/zero.

Taking the above example, if the GrowthSeed is set to 10 PJ (higher than the existing capacity of 7.7 PJ), the MaxCapacityGrowth constraint will be applied as follows: 10 x (1 + 0.2)⁵ - 4.9 = 19.9 PJ.

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. Must be between 0 and 1.

MinimumServiceFactor (optional, default = 0)

Is the minimum 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. Must be between 0 and 1 and be smaller or equal than the UtilizationFactor. It is used to define the minimum service level that a technology must provide due to, typically, technical or efficiency constraints.

efficiency (optional)

represents the technology efficiency. Required when using the “efficiency” agent objective, which ranks investment options according to their energy or material efficiency (see Agents).

Type (optional)

defines the type of a technology. Required when using the “similar_technology” search space, which allows agents to filter for technologies of a similar type (see Agents).

InterestRate

is the technology interest rate (called hurdle rates in other models). This is used for the interest used in the discount rate and corresponds to the interest built when borrowing money.

Agent0, …, AgentN

represent the proportion of initial capacity allocated to each agent. Must match AgentShare names specified in the Agents file. All agents must be represented in the table. If using “New” and “Retrofit” agents, you should create a column with the name of each “Retrofit” agent share. If only using “New” agents, you should create a column with the name of each “New” agent share. The value corresponds to the ownership of the initial stock, as defined in the Existing Sectoral Capacity for the starting year of the simulation.

For example, in a one-agent simulation, you should specify the following to indicate full ownership of existing capacity by the agent (assuming an agent share name of “Agent1”):

Techno-data: AgentShare - 1 agent

ProcessName	RegionName	Time	…	Agent1
resBoilerElectric	region1	2010	…	1
resBoilerElectric	region1	2030	…	1

In a two-agent simulation, assuming a 30% / 70% split of initial capacity between the two agents, the table would be as follows:

Techno-data: AgentShare - 2 agents

ProcessName	RegionName	Time	…	Agent1	Agent2
resBoilerElectric	region1	2010	…	0.3	0.7
resBoilerElectric	region1	2030	…	0.3	0.7

Values must sum to 1 for each row of the table.

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. The additional years at which input data for techno-data are defined need to equal for Commodities and Techno-data Timeslices.